Dissertations / Theses on the topic 'Multiple Criteria Decision Making (MCDM)'

This thesis addresses the topic of real-time decision making by driverless (autonomous) city vehicles, i.e. their ability to make appropriate driving decisions in non-simplified urban traffic conditions. After addressing the state of research, and explaining the research question, the thesis presents solutions for the subcomponents which are relevant for decision making with respect to information input (World Model), information output (Driving Maneuvers), and the real-time decision making process. TheWorld Model is a software component developed to fulfill the purpose of collecting information from perception and communication subsystems, maintaining an up-to-date view of the vehicle’s environment, and providing the required input information to the Real-Time Decision Making subsystem in a well-defined, and structured way. The real-time decision making process consists of two consecutive stages. While the first decision making stage uses a Petri net to model the safetycritical selection of feasible driving maneuvers, the second stage uses Multiple Criteria Decision Making (MCDM) methods to select the most appropriate driving maneuver, focusing on fulfilling objectives related to efficiency and comfort. The complex task of autonomous driving is subdivided into subtasks, called driving maneuvers, which represent the output (i.e. decision alternatives) of the real-time decision making process. Driving maneuvers are considered as implementations of closed-loop control algorithms, each capable of maneuvering the autonomous vehicle in a specific traffic situation. Experimental tests in both a 3D simulation and real-world experiments attest that the developed approach is suitable to deal with the complexity of real-world urban traffic situations.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Griffith School of Engineering
Science, Environment, Engineering and Technology
Full Text

Decision making study has been the multi-disciplinary research involving operations researchers, management scientists, statisticians, mathematical psychologists and economists as well as others. This study aims to investigate the theory and methodology of decision making research and apply them to different contexts in real cases. The study has reviewed the literature of Multiple Criteria Decision Making (MCDM), Evidential Reasoning (ER) approach, Naturalistic Decision Making (NDM) movement, Social Judgment Theory (SJT), and Adaptive Toolbox (AT) program. On the basis of these literatures, two methods, Evidence-based Trade-Off (EBTO) and Judgment Analysis with Heuristic Modelling (JA-HM), have been proposed and developed to accomplish decision making problems under different conditions. In the EBTO method, we propose a novel framework to aid people s decision making under uncertainty and imprecise goal. Under the framework, the imprecise goal is objectively modelled through an analytical structure, and is independent of the task requirement; the task requirement is specified by the trade-off strategy among criteria of the analytical structure through an importance weighting process, and is subject to the requirement change of a particular decision making task; the evidence available, that could contribute to the evaluation of general performance of the decision alternatives, are formulated with belief structures which are capable of capturing various format of uncertainties that arise from the absence of data, incomplete information and subjective judgments. The EBTO method was further applied in a case study of Soldier system decision making. The application has demonstrated that EBTO, as a tool, is able to provide a holistic analysis regarding the requirements of Soldier missions, the physical conditions of Soldiers, and the capability of their equipment and weapon systems, which is critical in domain. By drawing the cross-disciplinary literature from NDM and AT, the JA-HM extended the traditional Judgment Analysis (JA) method, through a number of novel methodological procedures, to account for the unique features of decision making tasks under extreme time pressure and dynamic shifting situations. These novel methodological procedures include, the notion of decision point to deconstruct the dynamic shifting situations in a way that decision problem could be identified and formulated; the classification of routine and non-routine problems, and associated data alignment process to enable meaningful decision data analysis across different decision makers (DMs); the notion of composite cue to account for the DMs iterative process of information perception and comprehension in dynamic task environment; the application of computational models of heuristics to account for the time constraints and process dynamics of DMs decision making process; and the application of cross-validation process to enable the methodological principle of competitive testing of decision models. The JA-HM was further applied in a case study of fire emergency decision making. The application has been the first behavioural test of the validity of the computational models of heuristics, in predicting the DMs decision making during fire emergency response. It has also been the first behavioural test of the validity of the non-compensatory heuristics in predicting the DMs decisions on ranking task. The findings identified extend the literature of AT and NDM, and have implications for the fire emergency decision making.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Aspectos econômicos, legais, ambientais e sociais tornam a Logística Reversa (LR) um assunto de destaque nos meios empresarial e acadêmico, considerando que sua função é a gestão dos processos de retorno de materiais, para tornar viável o reaproveitamento ou destino final adequado. Tendo em vista a movimentação de materiais existente nas redes logísticas existentes em clusters industriais, verifica-se na literatura a falta de estudos específicos referentes às operações de retorno associadas à LR. Por outro lado, os clusters industriais possuem reconhecida importância para economias regionais, por meio do fortalecimento de pequenas e médias empresas. Neste sentido, este trabalho teve por objetivo avaliar as atividades relacionadas à LR no cluster industrial calçadista de Juazeiro do Norte - CE, buscando identificar particularidades estruturais e gerenciais. Essas particularidades estão relacionadas a diversos fatores, e, além dos já citados, também são determinantes o tipo de produto e seus materiais constituintes, relações com stakeholders, tecnologia entre outros. O estudo foi desenvolvido por meio de pesquisa exploratória utilizando o método de estudo de caso, incluindo entrevistas e observações diretas. A análise foi feita utilizando um modelo de tomada de decisão multicritério que aplica o Analytic Network Process (ANP) e o Balanced Scorecard (BSC) para avaliar aspectos gerenciais estratégicos da LR. Utilizando-se a teoria da compatibilidade para quantificar o nível de similaridade entre vetores de decisão, os resultados obtidos foram comparados com respeito às diferenças entre unidades de estudo, assim como em relação aos dados mais gerais da indústria brasileira. Como resultados, identificou-se que as atividades da LR no cluster em foco são fortemente influenciadas pelas características do produto, por aspectos relacionados às aglomerações produtivas, no que se refere à economia e competitividade, assim como às diferenças existentes na gestão das empresas.
Economic, legal, environmental and social aspects turn Reverse Logistics (RL) an important subject in business and academic circles, considering that its function is managing processes of return of materials, to make feasible the reutilization or proper disposal. Taking into account the flow of materials in supply chain existing in industrial clusters, it is verified lack of specific studies regarding return operations associated with LR. On the other hand, industrial clusters are very important for regional economies, through strengthening of small and medium enterprises. In this sense, this work aims to evaluate the activities related to RL in the footwear industrial cluster of Juazeiro do Norte city, Ceará state, seeking to identify structural and managerial particularities. These particularities are related to several factors, and, in addition to those already mentioned, are also determinants the type of product and its constituent materials, relations with stakeholders, technology, and others. The study was developed through exploratory research using the case study method, including interviews and direct observations. In the analysis, was used a multicriteria decision-making model that applies the Analytic Network Process (ANP) and the Balanced Scorecard (BSC) to evaluate strategic managerial aspects of LR. Using the theory of compatibility to quantify the level of similarity between decision vectors, the results obtained were compared with respect to the differences between study units, as well as in relation to the more general data of the Brazilian industry. As a result, it was identified that the activities of LR in the cluster in focus are strongly influenced by the characteristics of the product, aspects related to productive agglomerations respect to economy and competitiveness, as well as differences in management of the companies.

For a little over twenty years, researchers have worked on integrating multi-criteria aggregation procedures (MCAP) to GIS. Several notable contributions have brought this field to what it is today. After studying the course of MCDA-GIS integration through several works, we question the future of such an attempt. Indeed most works that aim for an integration do not survive long after their direct purpose has been fulfilled. We end up understanding through a critical review of the existing systems that technical integration means nothing if it is not visible to the user on an operational level.

We therefore propose several contributions to improve the usability of MCDA methods in a geographic context. One of our works consists in adapting the PROMETHEE-GAIA methodology to be used on maps for spatially referenced problems. To do so, we define symbols/glyphs that display select parts of the results obtained through the PROMETHEE and GAIA methods. This allows for the comparison of alternatives' profiles and characteristics based on their geographic location which wasn't possible before. This adaptation helps us combine multicriteria and geographic aspects in an entirely new way.

We also propose some extensions of the GAIA method to improve the quality of the results and reduce the risk of wrong interpretations to be made due to losses of data.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished

Capes
A correta determinação de mercados internacionais pode ser um diferencial para expansão de negócios em empresas exportadoras. Entretanto, essa determinação de parceiros comerciais atrativos não é uma tarefa simples, tornando-se necessário o aprofundamento da abordagem, que é uma das extensões do Marketing e Comércio Exterior, chamado de International Market Selection (IMS), ou Seleção de Mercados Internacionais. Neste cenário, essa dissertação analisou os métodos existentes e seus principais autores e propôs a hipótese de que a teoria Multi-criteria Decision Analysis (MCDA) junto ao método ELECTRE II podem apresentar uma resposta positiva às lacunas encontradas neste cenário. Em resumo, os métodos existentes deixam indagações relativas: a) à praticidade de execução no cenário empresarial; b) à consideração da capacidade interna da empresa em exportar para o país-destino; c) à adaptação das metodologias com as singularidades das empresas no Brasil; d) à apresentação de uma ordenação dos países com potencial para exportação, considerando os múltiplos critérios existentes nessa análise. Assim, esta dissertação constrói um modelo de IMS, com ênfase nas empresas brasileiras. Esse modelo é ilustrado através de uma aplicação em uma empresa exportadora do sul do Brasil. Como resultados, apresenta-se uma ordem dos países com maior atratividade segundo as preferências, necessidades e limitações da empresa pesquisada. Foi descoberto que Argentina, Paraguai e Peru apresentam melhor compromisso com o exportador e, portanto, são os melhores destinos para estes produtos quando negociados por esta empresa.
The correct determination of international markets can be central for business expansion in exporting companies. However, this determination of attractive trading partners is not a simple task, making it necessary to deepen the approach, which is one of the extensions of Marketing and Foreign Trades, called the International Market Selection (IMS). In this scenario, this dissertation analyzed the existing methods and their main authors and proposed the hypothesis that the Multi-criteria Decision Analysis (MCDA) and the method ELECTRE II can present a positive response to the gaps found in this scenario. In summary, the existing methods leave inquiries regarding: a) the practicality of execution in the business scenario; B) consideration of the internal capacity of the company to export to the destination country; C) adapting the methodologies to the singularities of companies in Brazil; D) the presentation of an ordering of countries with export potential, considering the multiple criteria in this analysis. Thus, this dissertation builds a model of IMS, with emphasis on Brazilian companies. This model is illustrated by an application in an exporting company in the south of Brazil. As results, an order of the countries with more attractiveness according to the preferences, needs and limitations of the searched company is presented. It has been found that Argentina, Paraguay and Peru have a better commitment to the exporter and therefore are the best destinations for these products, when negotiated by this company.

PROMETHEE II is a widely used outranking method in the field of multi criteria decision aid (MCDA) method. The method outputs a ranking of a considered set of alternatives, based on the computation of net flow scores.

In this thesis, aggregating several published journal articles and conference papers, we propose three contributions that relate to the method: 1) Outranking methods are based on the pairwise comparison of all considered alternatives, yielding a quadratic time complexity for evaluating the net flow scores. We propose a method for reducing to a linear time complexity and show that it offers good results; 2) Determining preference parameters, i.e. relative weights for each criterion, is not a trivial task. We propose two complementary approaches to eliciting preferences, based on the aggregation-disaggregation paradigm; 3) The phenomenon of rank reversal, that also affects the PROMETHEE II method, is often considered as problematic in the MCDA community. We formalise the exact conditions for rank reversal to occur with PROMETHEE II when adding or removing one or more alternatives to the original set. These conditions lead to the exact bound of rank reversal, a way to determine the actions that actually provoke rank reversal and two associated metrics that should be useful for concrete applications.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished

Because of the increasing demand for the provision of energy worldwide and the numerous damages caused by a major use of fossil sources, the contribution of renewable energies has been increasing significantly in the global energy mix with the aim at moving towards a more sustainable development. In this context, this work aims at the development of a general methodology for designing PV systems based on ecodesign principles and taking into account simultaneously both techno-economic and environmental considerations. In order to evaluate the environmental performance of PV systems, an environmental assessment technique was used based on Life Cycle Assessment (LCA). The environmental model was successfully coupled with the design stage model of a PV grid-connected system (PVGCS). The PVGCS design model was then developed involving the estimation of solar radiation received in a specific geographic location, the calculation of the annual energy generated from the solar radiation received, the characteristics of the different components and the evaluation of the techno-economic criteria through Energy PayBack Time (EPBT) and PayBack Time (PBT). The performance model was then embedded in an outer multi-objective genetic algorithm optimization loop based on a variant of NSGA-II. A set of Pareto solutions was generated representing the optimal trade-off between the objectives considered in the analysis. A multi-variable statistical method (i.e., Principal Componet Analysis, PCA) was then applied to detect and omit redundant objectives that could be left out of the analysis without disturbing the main features of the solution space. Finally, a decision-making tool based on M-TOPSIS was used to select the alternative that provided a better compromise among all the objective functions that have been investigated. The results showed that while the PV modules based on c-Si have a better performance in energy generation, the environmental aspect is what makes them fall to the last positions. TF PV modules present the best trade-off in all scenarios under consideration. A special attention was paid to recycling process of PV module even if there is not yet enough information currently available for all the technologies evaluated. The main cause of this lack of information is the lifetime of PV modules. The data relative to the recycling processes for m-Si and CdTe PV technologies were introduced in the optimization procedure for ecodesign. By considering energy production and EPBT as optimization criteria into a bi-objective optimization cases, the importance of the benefits of PV modules end-of-life management was confirmed. An economic study of the recycling strategy must be investigated in order to have a more comprehensive view for decision making.

Modern planning theories encourage approaches that consider different stakeholders with a variety of discourse types and values to minimise politically motivated and single interest dominated decisions. Quantitative approaches such as Multi-criteria Decision Making (MCDM) techniques combined with GIS have been applied successfully in a number of land suitability analysis and environmental planning and management scenarios. The use of spatial MCDM techniques can improve the transparency and analytic rigor of the future land use decisions. In the last decade, applications of the MCDM techniques in GIS-based land suitability procedures have increased, however, applying these techniques at large-scale planning processes is rare. This highlights the need for examining how quantitative approaches such as MCDM techniques can integrate and therefore improve local planning and decision-making outcomes. This study is considered to be the first that by using a realistic and detailed set of criteria and group decision making, compares two MCDM techniques (analytical hierarchy procedure (AHP) Fuzzy AHP) in defining the extent of land-use zones at a large scale in Australia. The presented approach is particularly helpful in situation where local decision-makers are left with considerable room for discretion during the political transitions. Consequently, this research examines the application of MCDM methods in local land use planning for a 17,500 ha area, controlled by four local government areas (LGAs) in the northeast Gold Coast, located in southeast Queensland, Australia.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Griffith School of Environment
Science, Environment, Engineering and Technology
Full Text

Despite the number of approaches established for Multiple Criteria Optimisation Problems, few of them have been developed for the decision making process. This research work proposes a new methodology for the solution of optimisation problems that involve multiple criteria emphasising the Decision-Maker's (DM's) preferences model and the use of evolutionary computation techniques and fuzzy logic. The use of genetic algorithms (GAs) is of vital importance to the development of this research. The use of operations research (OR) techniques and decision analysis is also considered vital. The aim of this project is to provide a definition of hybrid approaches that combine the strengths of GA and decision analysis. For this reason four hybrid models are proposed: 1. The GA-SEMOPS. 2. The fuzzy multiobjective genetic optimiser. 3. The GA-PROTRADE. 4. The interactive procedure for multiple objective optimisation problems. The main characteristics of these approaches are that they handle the DM's preferences in an interactive way and their objective functions are formulated using goal levels and surrogate functions. In order to demonstrate that these models can be used in different optimisation problems they have been applied to different case studies covering examples from environmental systems to land and human resource allocation. Each model was studied in depth, comparing the results found with those available in literature. In the majority of the cases, it was found that they performed better than existing methods. The investigations carried out showed that the proposed hybrid models can be considered as a very powerful tool for the solution of a wide variety of optimisation problems in situations from business to science and engineering.

Background: Despite the competition for achieving lower costs and higher profits, companies are nowadays becoming increasingly aware of the environmental and social impacts of their operations. This is unveiled by growing numbers of sustainable activities in companies’ reports. Companies’ are also under more pressure from authorities and public to increase their business’s environmental performance, a so-called sustainable management process. Besides the pressure for developing environmental responsible activities, companies still remain with their low cost measures. Hence, they are concerned with the issue of identifying suitable measures to assess their sustainability.Supplier selection, processes by which companies evaluate, select and maintain their suppliers, regarded as one of the major operations affecting companies sustainable performance. While supplier selection was often performed in the past using conventional measures, there is an essential need to develop a framework for sustainable supplier selection in supply chain. By doing this research the company can ensure its operations are in line with environmental and social regulations and requirements. Research questions: - What is the important and applicable sustainable supplier evaluation criteria (SSEC) that could be applied? - What Multi criteria decision making method (MCDM) is suitable for evaluating and ranking the suppliers? - How would Renault group in Iran rank the supplier against the sustainable supplier evaluation criteria (SSEC)? - Which Sustainable supplier evaluation criteria (SSEC) could help the lowest ranked supplier to improve its sustainability performance? Purpose: The purpose of this research is to develop important and applicable sustainable supplier evaluation criteria (SSEC) and find out the multi criteria decision making method (MCDM) for ranking the suppliers. Furthermore, it also suggests to the manger to improve the sustainability performance of lower ranked suppliers. Method: The empirical data and the conclusions made from Renault Group in Iran are based on qualitative case study. This thesis is written from a positivistic perspective with a deductive approach. Conclusions: The main conclusions of this study are as below: - Developing a comprehensive list of attributes including the most important and applicable Sustainable Supplier Evaluation Criteria (SSEC) for evaluating sustainability performance of supplier for Renault Company in Iran. - TOPSIS is evaluated MCDM method to rank the suppliers against SSEC in Renault group in Iran. - The suppliers of the company are ranked and the best and the weakest supplier are determined using the TOPSIS. - The lowest ranked supplier is showed which SSEC could improve its performance by applying a parametric analysis.

Significant investments are being made in the construction sector in order to raise the quality of the buildings and make them more sustainable and energy-efficient. The key aspect of these investments should be the purposeful optimization of the possible renovation and construction measures. However, this important matter usually is being pushed aside in favor of construction price and/or quality. Nevertheless, there are plenty of criteria that play a major role in building sustainable development. The main purpose of this study is to present a tool that combines multi-criteria decision making (MCDM) methods and building certification systems in order to make weighted decisions in complicated construction tasks. For this, a decision making model was developed with a focus on sustainability, buildings’ life cycle, MCDM methods, and building certification. The first section of this thesis, the introduction, discusses the importance of the investigated area, and the main objectives, tasks, and structure of the thesis. A literature review is presented in Section 2 – Theory. The main works in the area of sustainability, LCA, building certification, and MCDM are collected to show their role and importance and how they interact in the construction industry. Section 3 presents and discusses the main ideas and instructions of the proposed decision making model. Section 4 (Methodology) introduces the main existing and proposed techniques that I have used to implement the study. Sections 5 and 6 are the case studies, which demonstrate how the proposed methods can be used in practice. Final conclusions and recommendations are presented in Section 7.

QC 20170209

Funded by L.E. Lundberg foundation

In this study, an integrated solution methodology for a general discrete multi-criteria decision making problem is developed based on the well-known outranking method Promethee II. While the methodology handles the existence of interdependency between the criteria, it can also incorporate the prospect theory in order to correctly reflect the decision behavior of the decision maker. A software is also developed for the application of the methodology and some applications are performed and presented.

Thesis (Ph. D.)--Ohio State University, 2001.
Title from first page of PDF file. Document formatted into pages; contains xiv, 169 p.; also contains graphics (some col.). Includes abstract and vita. Advisor: B. Chandresekaran, Dept. of Computer and Information Science. Includes bibliographical references (p. 165-169).

Aquesta tesi presenta una nova metodologia per resoldre problemes de presa de decisions. Hem
estudiat els casos en què cal considerar més d'un criteri. Aquests tipus de mètodes de decisió es
coneixen com MCDM (Multiple Criteria Decision Making), o també MCDA (Multiple Criteria
Decision Aid). La diferència entre simplement "prendre decisions" o "ajudar a prendre
decisions" recau en si el mètode es dissenya per recomanar la decisió a prendre o si també
inclou elements que permeten entendre com es prenen les decisions en un cert context. La nostra
proposta inclou elements dels dos plantejaments. D'una banda, hem intentat que la persona que
ha d'usar el mètode no necessiti aprendre tècniques complexes abans de poder-lo aplicar a casos
reals. D'altra banda, el mètode no és una caixa negra, sinó que l'usuari rep informació sobre
característiques de les dades que ha de tenir en compte abans de fer la decisió final.
ClusDM és un mètode de presa de decisions pensat per resoldre dos tipus concrets de
problemes: (i) ordenar un conjunt d'alternatives de la millor a la pitjor, (ii) seleccionar les
millors alternatives del conjunt. La dificultat d'aquest procés recau en que cal maximitzar
diversos criteris parcials (i normalment no correlacionats) al mateix temps. A la tesi es pot
trobar un resum de les diferents aproximacions a aquest tipus de problemes de decisió. Només
destacar que el nostre mètode segueix les bases de la Teoria de la Utilitat.
Els mètodes clàssics consideren només criteris numèrics. Diferents extensions a aquests models
s'han anat desenvolupant durant els últims anys. En aquesta tesis ens hem plantejat la
possibilitat de tenir criteris que utilitzin diferents tipus de valors. A més, hem afegit dues fases a
la metodologia habitual (que té una fase d'agregació i una d'ordenació), que són: l'explicació
del resultat i l'avaluació de la qualitat.
La "Fase d'explicació" està dedicada a assignar un terme lingüístic per descriure cada
alternativa segons la seva posició en el ranking. L'ús de vocabularis qualitatius facilita la
comprensió del resultat. El significat dels diferents termes usats ve donat per una funció de
negació. Aquesta representació es basa en contrastar el significat d'un terme amb el dels termes
oposats (els seus antònims).
La "Fase d'Avaluació de la Qualitat" analitza a fons els resultats intermedis obtinguts en els
diferents passos del procés i intenta mesurar l'error acumulat. ClusDM proporciona diverses
mesures de qualitat parcial per cada fase del procés, de manera que l'usuari tingui constància de
la confiança que pot donar al resultat final que doni el sistema.
This thesis presents a new methodology for decision making. In particular, we have studied the
problems that consider more than one criterion, which is known as Multiple Criteria Decision
Making (MDCM) or Multiple Criteria Decision Aid (MCDA). The difference relies on the fact
of imitating the behaviour of the decision maker (i.e. develop a method that makes decisions) or
giving to the decision maker some additional information that allows him to understand the
mechanism of solving decisions (i.e. the decision maker can learn from the use of the method).
Our proposal fits better in the MCDA approach, but has also similarities with the MCDM
perspective. On one hand, the method we have designed is independent enough to not require a
deep understanding of the process by the decision maker. On the other hand, we have carefully
studied the process and the method is able to extract knowledge about the decision problem,
which is given to the user to let him know any special characteristics of the data analysed.
ClusDM is a new method to solve multicriteria decision problems. It is able to find a ranking of
alternatives or to select the best ones. This process is not easy since usually it is not possible to
maximise all the partial profits (i.e.criteria) at the same time. In the thesis we present an
overview of the large amount of methods developed to solve this problem. We follow the utility
theory approach.
Classical methods consider only numerical criteria. Some extensions allow the consideration of
other scales, such as, fuzzy or ordinal values, but usually they are required to have a common
scale for all criteria. This thesis faces the problem of managing different types of criteria at the
same time. Methods following the utility approach consider two steps to sort a decision
problem out: the aggregation and the ranking. We have included some additional steps in order
to improve the process: (i) the explanation phase and (ii) the quality measurement phase.
In the "Explanation Phase", special attention is devoted to give an appropriate linguistic
description of the ranking. The necessity to give a qualitatively described result has been argued
by different authors. The rationale behind this belief is that human decision makers understand
better a linguistic statement characterising the selected alternative (or ranking of alternatives)
than a numerical result or even a membership function. In this context, a new negation-based
semantics has been studied. The key idea is that we can infer the meaning of a term knowing the
terms that express an opposite value. The use of this new semantics representation seems
appropriate to obtain a result that can be easily understood by the decision maker.
In the "Quality Measurement Phase", different quality measures for each stage of the process
are calculated. With these measures we can give an overall value of the trustworthiness of the
final result. This kind of information is very useful for the decision maker in order to pay more
or less attention to the recommendations of the system.

Hundreds of thousands of home users are victimized by cyber-attacks every year. Many experts agree that average home users are not doing enough to protect their home computers from cyber-attacks. Improperly managed home computers can lead to individuals losing data, systems performing slowly, identity loss or theft, and ransom payments. En masse attacks can act in concert to infect personal computers in business and government. Home users currently receive conflicting guidance, often in the form of recommendations such as 'Top 10’ lists which are not appropriate for their specific needs. In many instances users ignore all guidance. Often, these ‘Top 10’ lists appear to be based solely on subjective opinion. Ultimately, the researchers asked themselves the following question: how can we provide home users with better guidance for determining and applying appropriate security controls that meet their needs and can be verified by the cyber security community? This praxis proposes a methodology for determining and prioritizing the most appropriate security controls for home computing. Using Multi Criteria Decision Making (MCDM) and subject matter expertise, this praxis identifies, analyzes and prioritizes security controls used by government and industry to determine which controls can substantively improve home computing security. This praxis will then apply our methodology using examples to demonstrate its benefits.

The proposal generalization of expert estimates concordance idea for the case of nonlinear preferance function guaranties on optimal concordance of mesuarement and expert data, whereas machine learning approach ensure the possibility of more accurate approximation expert preference function with complex structure.
Предложен подход согласования экспертных оценок для случая нелинейных функций предпочтения, который гарантирует оптимальное согласование данных измерений и экспертных данных, который при использовании методов машинного обучения обеспечивает возможность построения более точной аппроксимационной функции предпочтений эксперта.

The real estate selection process might be regarded as a typical Multi-Criteria Decision Making (MCDM) problem. With current literature concentrating predominantly on institutional investment decision making, additional effort should be directed towards studying inexperienced homebuyers who want to buy a property in which to live. In this context, authors have described the decision environment as a complex decision process with restricted access to property data, high financial burdens partially due to the illiquid nature of the investment, the unfamiliarity with the decision task and low transparency in information aggregation. Consequently, this situation could benefit from a more structured approach that assists homebuyers in their actions. In order to guide the decision making process and provide a suitable support mechanism, it is necessary to first structure the problem and extract the required information. A thorough literature review shows that little guidance is available for MCDM problem structuring. Consequently, this research first proposes an MCDM problem-structuring framework to decompose complex problems into smaller parts. Foremost, the application is intended for high-involvement consumer products and services. This framework is derived from MCDM and methodology literature, where the former provides the elements that need to be defined in any MCDM problem situation, and the latter suggests suitable data collection and analysis methods to obtain the information. As a result, the first contribution to existing literature is the introduction of an MCDM problem-structuring framework, which consists of a carefully designed sequential exploratory mixed method procedure. Next, following the proposed structure, the real estate selection problem in Majorca (Spain) is defined. Whilst providing the inherent problem elements and establishing a comprehensive list of evaluation criteria to assess luxury properties, the fieldwork also offers behavioural insights, contributing and supplementing existing real estate research. In particular, major misunderstandings and false assumptions during real estate agent and client interactions are observed, stressing the need to optimise communication and targeting strategies. On the basis of the relevant real estate evaluation criteria, a dataset of alternative houses is created and subsequently rated by prospective luxury-homebuyers. This provides the basis for the third research focus, the construction of a decision support model for real estate selection. In accordance to the problem features and model requirements, the Evidential Reasoning (ER) rule is identified to offer a powerful and transparent evidence aggregation process, with the potential to have a superior performance than other methods in addressing the selection decision. Due to the ER rule’s short history (2013), application studies in general are practically non-existing and unprecedented in the real estate domain. Therefore, the use of a modified ER model can provide the real estate literature with a prescriptive multi-criteria decision support mechanism, whilst simultaneously offering an application study for the MCDM community and other relevant decision analysis domains. In closing, modelling a real problem using the ER rule highlights the method’s advantages and might in turn increase awareness, leading to more applications.

Thesis (M.Phil.)--City University of Hong Kong, 2005.
"Submitted to Department of Building and Construction in partial fulfillment of the requirements for the degree of Master of Philosophy" Includes bibliographical references (leaves 239-241)

Aerospace systems are complex systems with interacting disciplines and technologies. As a result, the Decision Makers (DMs) dealing with such problems are involved in balancing the multiple, potentially conflicting attributes/criteria, transforming a large amount of customer supplied guidelines into a solidly defined set of requirement definitions. A variety of existing decision making methods are available to deal with this type of decision problems. The selection of a most appropriate decision making method is of particular importance since inappropriate decision methods are likely causes of misleading engineering design decisions. The research presented in this dissertation proposes a knowledge-based Multi-criteria Interactive Decision-making Advisor and Synthesis process (MIDAS), which can facilitate the selection of the most appropriate decision making method and which provides insight to the user for fulfilling different preferences. Once the most appropriate method is selected for the given problem, the advisor is also able to aid the DM to reach the final decision by following the rigorous problem solving procedure of the selected method. The MIDAS can also provide guidance as to the requirements needed to be fulfilled by a potentially new method for cases where no suitable method is found. In many other domains, such as complex system operation, decisions are often made in an environment with continuously changing situations. In addition, the decisions are usually completed based on uncertain or incomplete information due to the data availability and the environmental variation. This fact exacerbates the complexity of the decision making process because it results in the difficulties in perfectly and deterministically reasoning about the effects of the decisions and thus make it hard in determining the further decisions. In order to make proper decision and increase the system’s effectiveness, an advanced decision strategy is needed to capture the system’s dynamic characteristics and environmental uncertainty. An autonomous decision making advisor is developed to perform the real-time decision making under uncertainty. The development of the advisor system aims to solve a resource allocation problem to redistribute the limited resources to different agents under various scenarios and try to maximize the total rewards obtained from the resource allocation actions.

Thesis (MBA)--Stellenbosch University, 2003.
ENGLISH ABSTRACT: One of the most difficult and more important decisions taken by a client is the selection of the most appropriate contractor. It requires the assessment of various factors, often conflicting, in order to determine the most appropriate contractor and are therefore classified as a problem that can be resolved by using multiple criteria decision making methods. The act of decision making is never an easy one and requires a sound understanding of the requirement, the alternatives and the model used to assess the alternatives in terms of the requirement in order to instil confidence that the most appropriate alternative is selected. The appropriateness of the methods used in contractor evaluation has a vital impact on the cost of the transaction. The three broad categories, or schools of thought, relating to multiple criteria decision making (MCDM) methods are assessed in terms of their applicability to the contractor selection problem within a quasi-government organisation, namely Armscor. Of the three categories, only the methods of the value measurement category were found to be appropriate within the current legislative framework of the Preferential Procurement Act, which seeks to express the performance of an offer as a unique numerical function. The old contractor selection model of direct point allocation on a qualitative scale is shown to be inappropriate, especially in terms of the additive utility assumption of single dimensional units. The proposed new model makes use of the weighted product model that is not restricted by the additive utility assumption as it results in dimensionless analysis of the criteria. The utility functions associated with the quantitative criteria uses curves which are raised to the power of the confidence variable. The arithmetic mean of these variables represents the group’s confidence level associated with each contractor’s offer in the correctness and/or its ability to maintain the stated level of performance. Furthermore, the analytic hierarchy process is used for the assessment of the qualitative criteria. The new model, although not perfect, is an improvement over the old model with regards to the understanding of the requirement as well as the assessment of contractors’ proposals.
AFRIKAANSE OPSOMMING: Die keuse van ‘n kontrakteur is een van die moeilikste besluite wat ‘n kliënt moet neem, dit is egter ook een van die belangrikste besluite wat geneem word. Ten einde die mees geskikte kontrakteur te kies, moet daar ‘n waarde geheg word aan verskeie faktore, menigmaal teenstrydig, wat kontrakteur seleksie klassifiseer as ‘n probleem wat deur middel van meervoudige-kriteria-besluitnemingsmetodes opgelos kan word. Die handeling van besluitneming is nooit ‘n maklike een en vereis deeglike kennis van die behoefte, die alternatiewe, asook die model wat gebruik word om die alternatiewe in terme van die behoefte te waardeer in orde om vertroue in die gekose alternatief te hê. Vir die doeleindes van hierdie studie is die drie kategorieë van meervoudige-kriteria-besluitnemingsmetodes vergelyk in terme van hul toepaslikheid op die voorafgenoemde probleem binne ‘n Semi-Staatsinstelling, naamlik Krygkor, met die oogmerk om die beste metode te identifiseer. Slegs die metodes vervat in die waarde-meting kategorie is geskik binne die Wet op die Raamwerk vir Voorkeurverkrygingsbeleid wat die evaluasie van ‘n aanbod uitdruk as ‘n unieke numeriese funksie. Uit die studie blyk dit dat die vorige kontrakteur seleksie model van direkte punt allokasie op ‘n kwalitatiewe skaal onvanpas is, veral in terme van die sommerings-nutfunksie aanname van enkel dimensionele eenhede. Die model wat eerder aanbeveel word, maak gebruik van die geweegde-produk-model wat nie beperk word deur die bogenoemde aanname nie, aangesien dit dimensielose analise tot gevolg het. Nutfunksies wat geassosieër word met kwantitatiewe kriteria, word voorgestel deur kurwes wat tot die mag van die vertrouensvlak-veranderlike gehef word. Die rekenkundige gemiddelde van hierdie veranderlike verteenwoordig die groep se vertrouensvlak met betrekking tot elke kontrakteur se akkuraatheid en vermoeë om die gespesifiseerde vlak van werkverrigting te handhaaf. Die kwalitatiewe kriteria word beoordeel deur gebruik te maak van die analitiese hiërargie proses. Die gevolgtrekking wat uiteindelik gemaak word is dat die nuwe model, alhoewel nie foutloos, tog ‘n verbetering is op die vorige model, veral met betrekking tot die insig wat verkry word deur die ontleding van die kontrakteurs se voorstelle in terme van die bepaalde behoefte wat bevredig moet word, ten einde die beste keuse uit te oefen.

[EN] The main objectives of this research are the following. First, to analyse the models and methods in Decision Support Systems (DSS) for forest management, taking into account the important features which allow forestry related problems to be categorized. Second, to define strategic criteria for the sustainable management of Mediterranean forests, as well as to elicit and aggregate the stakeholders' preferences. Third, to propose a robust methodology to implement collaborative management focused on ESS and to develop indicators for the main functions of ESS. The methodology is based on a workshop and surveys to elicit the decision makers', experts' and other stakeholders' preferences. Several techniques were then used to aggregate individual judgements and determine social preferences, in particular, Analytic Hierarchy Process (AHP) and Goal Programming (GP). In addition, a PROMETHEE based method has been developed to provide indicators of the ESS, classified into provisioning, maintenance and direct to citizens services. The analysis of DSS for forest management has shown that the best choice of approach to solve a given problem depend on its nature, which can be characterized by the temporal scale, spatial context, spatial scale, number of decision makers or stakeholders, objectives and finally goods and services involved. A decision hierarchy for strategic management of Valencian forests has been developed by involving experts during the design phase. This was later validated in consultation with the stakeholders in a workshop and provides the base from which to obtain the social preferences. The results show greater importance for environmental and social criteria and lesser relevance for economic criteria, valid for both public and private Mediterranean forests. This result is the same regardless of which preference aggregation technique was used and takes into account the preferences of the majority of the stakeholders and also the minority opinions furthest from the consensus. New products and services such as rural tourism, renewable energies, landscape, hydrological regulation and erosion control, biodiversity and climate change mitigation are relevant. This research also proposes a robust methodology to implement collaborative management focused on ESS provided by protected areas and aggregated indicators for their main functions. Decision makers, technical staff and other stakeholders are included in the process from the beginning, by identifying ESS and eliciting preferences using the AHP method. Qualitative and quantitative data are then integrated into a PROMETHEE based method in order to obtain indicators for provisioning, maintenance and direct to citizens services. This methodology, which has been applied in a forest natural park, provides a tool for exploiting available technical and social data in a continuous process, as well as graphical results, which are easy to understand. This approach also overcomes the difficulties found in prioritising management objectives in a multiple criteria context with limited resources and facilitates consensus between all of the people involved. The new indicators define an innovative approach to assessing the ESS from the supply perspective and provide basic information to help establish payment systems for environmental services and compensation for natural disasters.
[ES] Los principales objetivos de esta investigación son los siguientes. En primer lugar, analizar los modelos y los métodos de los sistemas de ayuda a la toma de decisiones para gestión forestal, teniendo en cuenta las características relevantes que permiten clasificar los problemas forestales. En segundo lugar, definir los criterios estratégicos para la gestión forestal sostenible del bosque mediterráneo, así como obtener y agregar las preferencias de los decisores y otras partes interesadas. En tercer lugar, proponer una metodología robusta para implementar una gestión colaborativa centrada en los servicios del ecosistema y desarrollar indicadores para las principales funciones de estos servicios. La metodología se fundamenta en una jornada de trabajo con decisores, expertos y otros grupos de personas interesadas, así como en encuestas a todos ellos. Después se han utilizado varias técnicas para agregar las preferencias individuales y determinar las preferencias de los distintos grupos sociales, en particular el proceso analítico jerárquico y la programación por metas. Adicionalmente, se ha desarrollado un método basado en PROMETHEE que permite obtener indicadores de los servicios del ecosistema, clasificados en servicios de producción, mantenimiento y directos a los ciudadanos. El análisis de los sistemas de ayuda a la toma de decisiones para gestión forestal ha puesto de manifiesto que los mejores enfoques para resolver los problemas forestales dependen de su naturaleza, caracterizada por la escala temporal, el contexto espacial, la escala espacial, el número de decisores o personas interesadas, el número de objetivos y por último los bienes y servicios involucrados. Se ha desarrollado una jerarquía de decisión para la gestión estratégica de los bosques valencianos involucrando a expertos en la fase de diseño. Este modelo fue validado posteriormente por las partes interesadas en una jornada organizada con esta finalidad y ha sido la base para obtener las preferencias sociales. Los resultados ponen de manifiesto la mayor importancia de los criterios medioambientales y sociales y la menor relevancia de los económicos, tanto para el monte mediterráneo público como privado. Este resultado es independiente del método de agregación utilizado y tiene en cuenta tanto las preferencias de la mayoría como de la minoría más alejada del consenso. Son relevantes los nuevos productos y servicios tales como el turismo rural, las energías renovables, el paisaje, la regulación hidrológica y el control de la erosión, la biodiversidad y la mitigación del cambio climático. Esta investigación también propone una metodología robusta para implementar una gestión colaborativa centrada en los servicios del ecosistema que proporcionan las áreas protegidas e indicadores agregados para sus principales funciones. Los responsables de las decisiones, el personal técnico y otras personas interesadas han participado desde el inicio del proceso, identificando los servicios del ecosistema y proporcionado sus preferencias mediante la técnica del proceso analítico jerárquico. Después se integran los datos cualitativos y cuantitativos en un método basado en PROMETHEE con la finalidad de obtener indicadores para los servicios de producción, mantenimiento y directos a los ciudadanos. Esta metodología, que se ha aplicado en un parque natural, facilita la explotación de los datos técnicos y sociales en un proceso continuo y proporciona resultados gráficos muy fáciles de entender. Este enfoque también permite superar las dificultades que surgen al priorizar los objetivos de gestión en un contexto multicriterio con recursos limitados y facilita el consenso entre todas las personas involucradas. Los nuevos indicadores representan un enfoque innovador para la valoración de los servicios del ecosistema desde el punto de vista de la oferta y proporcionan información básica para establecer sistemas de pagos por
[CAT] Els principals objectius d'aquesta recerca són els següents. En primer lloc, analitzar els models i els mètodes dels sistemes d'ajuda a la presa de decisions per a gestió forestal, tenint en compte les característiques rellevants que permeten classificar els problemes forestals. En segon lloc, definir els criteris estratègics per a la gestió forestal sostenible del bosc mediterrani, com també obtenir i agregar les preferències dels decisors i altres parts interessades. En tercer lloc, proposar una metodologia robusta per a implementar una gestió col·laborativa centrada en els serveis de l'ecosistema i desenvolupar indicadors per a les principals funcions d'aquests serveis. La metodologia es fonamenta en una jornada de treball amb decisors, experts i altres grups de persones interessades, i també en enquestes a tots ells. Després s'han utilitzat diverses tècniques per a afegir-hi les preferències individuals i determinar les preferències dels diferents grups socials, en particular el procés analític jeràrquic i la programació per metes. Addicionalment, s'ha desenvolupat un mètode basat en PROMETHEE que permet obtenir indicadors dels serveis de l'ecosistema, classificats en serveis de producció, manteniment i directes als ciutadans. L'anàlisi dels sistemes d'ajuda a la presa de decisions per a la gestió forestal ha posat de manifest que els millors enfocaments per a resoldre els problemes forestals depenen de la naturalesa d'aquests problemes, caracteritzada per l'escala temporal, el context espacial, l'escala espacial, el nombre de decisors o persones interessades, el nombre d'objectius i, finalment, els béns i serveis involucrats. S'ha desenvolupat una jerarquia de decisió per a la gestió estratègica dels boscos valencians involucrant experts en la fase de disseny. Aquest model ha sigut validat posteriorment per les parts interessades en una jornada organitzada amb aquesta finalitat i ha sigut la base per a obtenir les preferències socials. Els resultats posen de manifest la major importància dels criteris mediambientals i socials i la menor rellevància dels econòmics, tant per a la muntanya mediterrània pública com privada. Aquest resultat és independent del mètode d'agregació utilitzat i té en compte tant les preferències de la majoria com de la minoria més allunyada del consens. Són rellevants els nous productes i serveis, com ara el turisme rural, les energies renovables, el paisatge, la regulació hidrològica i el control de l'erosió, la biodiversitat i la mitigació del canvi climàtic. Aquesta recerca també proposa una metodologia robusta per a implementar una gestió col·laborativa centrada en els serveis de l'ecosistema que proporcionen les àrees protegides i indicadors agregats per a les seues funcions principals. Els responsables de les decisions, el personal tècnic i altres persones interessades hi han participat des de l'inici del procés, identificant els serveis de l'ecosistema i proporcionant les seues preferències mitjançant la tècnica del procés analític jeràrquic. Després s'integren les dades qualitatives i quantitatives en un mètode basat en PROMETHEE amb la finalitat d'obtenir indicadors per als serveis de producció, manteniment i directes als ciutadans. Aquesta metodologia, que s'ha aplicat en un parc natural, facilita l'explotació de les dades tècniques i socials en un procés continu i proporciona resultats gràfics molt fàcils d'entendre. Aquest enfocament també permet superar les dificultats que sorgeixen a l'hora de prioritzar els objectius de gestió en un context multicriteri amb recursos limitats i facilita el consens entre totes les persones involucrades. Els nous indicadors representen un enfocament innovador per a la valoració dels serveis de l'ecosistema des del punt de vista de l'oferta i proporcionen informació bàsica per a establir sistemes de pagaments per serveis ambientals i compensacions per desastres naturals.
Segura Maroto, M. (2015). ASSESSMENT OF ECOSYSTEM SERVICES BASED ON MULTIPLE CRITERIA AND GROUP DECISION MAKING [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/57955
TESIS

Thesis (M.B.A.)--Naval Postgraduate School, June 2008.
Thesis Advisor(s): Cuskey, Jeffrey. "June 2008." Description based on title screen as viewed on September 2, 2008. Includes bibliographical references (p. 75-80). Also available in print.

In modern organizations where managers must constantly be dealing with an overload of information, it is often observed that participants in group decision processes either are not clearly aware of their specific preferences or that they are not capable of properly formulating those preferences. When this happens, inconsistent or incomplete expression of personal preferences and their use in decision making may lead to an unjustifiable outcome for the group. Due to this problem, the strengths and effectiveness of GDSS-supported group meetings may, in some situations, not be apparent. This dissertation develops a new approach to supporting group decision making, focusing on preference knowledge of individual participants in a group. A system architecture for the design of an MCDM (Multiple Criteria Decision Making) GDSS which facilitates the process of eliciting, formulating, utilizing, aggregating, and analyzing preferences for individuals within groups is presented. The architecture integrates multi-criteria decision making paradigms with a group decision support environment. A prototype has been developed in order to demonstrate the design feasibility of an architecture that centers around four phases of choice making: alternative generation, preference specification, alternative evaluation, and preference aggregation. The prototype is designed to support managerial choice and judgment processes in collaborative meetings. The intended problem domain of the model is semi-structured managerial decisions for which decision variables (attributes) can be represented in quantitative terms to some extent, yet for which evaluation of alternatives requires a high degree of intuition and personal analysis. The process of prototyping the proposed architecture and the results from a qualitative study have provided some instructive conclusions relating to MCDM GDSS design: (1) support for human choice strategies can be integrated into a GDSS, (2) appropriate management of preferences of group participants will facilitate collaborative decision processes, (3) hierarchical decomposition of a decision problem can provide structure to a problem and thereby reduce problem complexity, and (4) managerial decisions are appropriate problems to which the current approach can be applied.

L’objectif de ce travail est de développer un cadre méthodologique et générique d’éco-conception de procédés chimiques couplant des outils de modélisation et de simulation traditionnels de procédés (HYSYS, COCO, ProSimPlus et Ariane), d’Analyse du Cycle de Vie (ACV), d’optimisation multiobjectif basée sur des Algorithmes Génétiques et enfin des outils d’aide à la décision multicritère (ELECTRE, PROMETHEE, M-TOPSIS). Il s’agit de généraliser, d’automatiser et d’optimiser l’évaluation des impacts environnementaux au stade préliminaire de la conception d’un procédé chimique. L’approche comprend trois étapes principales. Les deux premières correspondent d’une part aux phases d’analyse de l’inventaire par calcul des bilans de matière et d’énergie et d’autre part à l’évaluation environnementale par ACV. Le problème du manque d’information ou de l’imprécision dans les bases de données classiques en ACV pour la production d’énergie notamment sous forme de vapeur largement utilisée dans les procédés a reçu une attention particulière. Une solution proposée consiste à utiliser un simulateur de procédés de production d’utilités (Ariane, ProSim SA) pour contribuer à alimenter la base de données environnementale en tenant compte de variations sur les conditions opératoires ou sur les technologies utilisées. Des sous-modules « énergie » sont ainsi proposés pour calculer les émissions relatives aux impacts liés à l’utilisation de l’énergie dans les procédés. La troisième étape réalise l’interaction entre les deux premières phases et l’optimisation multi-objectif qui met en jeu des critères économiques et environnementaux. Elle conduit à des solutions de compromis le long du front de Pareto à partir desquelles les meilleures sont choisies à l’aide de méthodes d’aide à la décision. L’approche est appliquée à des procédés de production continus : production de benzène par hydrodéalkylation du toluène HDA et production de biodiesel à partir d’huiles végétales. Une stratégie à plusieurs niveaux est mise en oeuvre pour l'analyse de l'optimisation multi-objectif. Elle est utilisée dans les deux cas d'étude afin d'analyser les comportements antagonistes des critères
The objective of this work is to propose an integrated and generic framework for eco-design coupling traditional modelling and flowsheeting simulation tools (HYSYS, COCO, ProSimPlus and Ariane), Life Cycle Assessment, multi-objective optimization based on Genetic Algorithms and multiple criteria decision-making methods MCDM (Multiple Choice Decision Making, such as ELECTRE, PROMETHEE, M-TOPSIS) that generalizes, automates and optimizes the evaluation of the environmental criteria at earlier design stage. The approach consists of three main stages. The first two steps correspond respectively to process inventory analysis based on mass and energy balances and impact assessment phases of LCA methodology. Specific attention is paid to the main issues that can be encountered with database and impact assessment i.e. incomplete or missing information, or approximate information that does not match exactly the real situation that may introduce a bias in the environmental impact estimation. A process simulation tool dedicated to production utilities, Ariane, ProSim SA is used to fill environmental database gap, by the design of specific energy sub modules, so that the life cycle energy related emissions for any given process can be computed. The third stage of the methodology is based on the interaction of the previous steps with process simulation for environmental impact assessment and cost estimation through a computational framework. The use of multi-objective optimization methods generally leads to a set of efficient solutions, the so-called Pareto front. The next step consists in identifying the best ones through MCDM methods. The approach is applied to two processes operating in continuous mode. The capabilities of the methodology are highlighted through these case studies (benzene production by HDA process and biodiesel production from vegetable oils). A multi-level assessment for multi-objective optimization is implemented for both cases, the explored pathways depending on the analysis and antagonist behaviour of the criteria

Decision making is an essential activity for humans and often becomes complex in the presence of uncertainty or insufficient knowledge. This research aims at estimating preferences using pairwise comparisons. A decision maker uses pairwise comparison when he/she is unable to directly assign criteria weights or scores to the available options. The judgments provided in pairwise comparisons may not always be consistent for several reasons. Experimentation has been used to obtain statistical evidence related to the widely-used consistency measures. The results highlight the need to propose new consistency measures. Two new consistency measures - termed congruence and dissonance - are proposed to aid the decision maker in the process of elicitation. Inconsistencies in pairwise comparisons are of two types i.e. cardinal and ordinal. It is shown that both cardinal and ordinal consistency can be improved with the help of these two measures. A heuristic method is then devised to detect and remove intransitive judgments. The results suggest that the devised method is feasible for improving ordinal consistency and is computationally more efficient than the optimization-based methods. There exist situations when revision of judgments is not allowed and prioritization is required without attempting to remove inconsistency. A new prioritization method has been proposed using the graph-theoretic approach. Although the performance of the proposed prioritization method was found to be comparable to other approaches, it has practical limitation in terms of computation time. As a consequence, the problem of prioritization is explored as an optimization problem. A new method based on multi-objective optimization is formulated that offers multiple non-dominated solutions and outperforms all other relevant methods for inconsistent set of judgments. A priority estimation tool (PriEsT) has been developed that implements the proposed consistency measures and prioritization methods. In order to show the benefits of PriEsT, a case study involving Telecom infrastructure selection is presented.

Information technology (IT) investment decision makers are required to process large volumes of complex data. An existing body of knowledge relevant to IT portfolio management (PfM), decision analysis, visual comprehension of large volumes of information, and IT investment decision making suggest Multi-Criteria Decision Making (MCDM) and hypervariate display techniques can reduce cognitive load and improve decision confidence in IT PfM decisions. This dissertation investigates improving the decision confidence by reducing cognitive burden of the decision maker through greater comprehension of relevant decision information. Decision makers from across the federal government were presented with actual federal IT portfolio project lifecycle costs and durations using hypervariate displays to better comprehend IT portfolio information more quickly and make more confident decisions. Other information economics attributes were randomized for IT portfolio projects to generate Balanced Scorecard (BSC) values to support MCDM decision aids focused on IT investment alignment with specific business objectives and constraints. Both quantitative and qualitative measures of participant comprehension, confidence, and efficiency were measured to assess hypervariate display treatment and then MCDM decision aid treatment effectiveness. Morae Recorder Autopilot guided participants through scenario tasks and collected study data without researcher intervention for analysis using Morae Manager. Results showed improved comprehension and decision confidence using hypervariate displays of federal IT portfolio information over the standard displays. Both quantitative and qualitative data showed significant differences in accomplishment of assigned IT portfolio management tasks and increased confidence in decisions. MCDM techniques, incorporating IT BSC, Monte Carlo simulation, and optimization algorithms to provide cost, value, and risk optimized portfolios improved decision making efficiency. Participants did not find improved quality and reduced uncertainty from optimized IT portfolio information. However, on average participants were satisfied and confident with the portfolio optimizations. Improved and efficient methods of delivering and visualizing IT portfolio information can reduce decision maker cognitive load, improve comprehension efficiency, and improve decision making confidence. Study results contribute to knowledge in the area of comprehension and decision making cognitive processes, and demonstrate important linkages between Human-Computer Interaction (HCI) and Decision Support Systems (DSS) to support IT PfM decision making.

The concept of fuzzy multi criteria decision making process has received significant attention from research community due to its successful applications for human based decision making problems under fuzzy environment. It complements the decision makers to evaluate their subjective judgements under situations that are vague, imprecise, random and uncertain in nature. Inspired by such real applications, in this research study, the theoretical foundation of a hybrid fuzzy multi criteria decision making model based on new centroid defuzzification method is proposed. The proposed model tackles some issues that may be associated with the selection problems of the multi criteria decision making such as deriving decision criteria important weights, ranking various alternatives, suitable combination of fuzzy multi criteria decision making techniques and proper defuzzification method used. In developing the hybrid model, two multi criteria decision making techniques are integrated which are; 1) consistent fuzzy preference relations and; 2) fuzzy technique for order of preference by similarity to ideal solution. It is also incorporated together with new defuzzification method namely intuitive multiple centroid. In the view of evidence outlined in this study, the proposed model serves as a generic multi criteria decision making procedure, particularly when fuzzy sets are involved in the decision process. The two major contributions from this study are that: 1) The intuitive multiple centroid defuzzification capable to cater all possible representations of fuzzy sets reasonably and consistent with human intuition or judgment. 2) The generalised hybrid fuzzy multiple decision making model using intuitive multiple centroid gives better computation to evaluate criteria and alternatives in decision making problems under different uncertain environment. Furthermore, an empirical validation of the proposed model is investigated through conducting a case study of staff recruitment in MESSRS SAPRUDIN, IDRIS & CO, Malaysia. In this case study, a group of three decision makers, and four finalist of candidates are selected to take part of this case study. Their involvement achieved the first objective of the case study. At the end of the case study, a sensitivity analysis is conducted to indicate the robustness and the consistency of the results obtained. It is concluded that the proposed model is indeed beneficial under different environment.

The decision-making process in highway construction projects identifies and selects the optimal alternative based on the user requirements and evaluation criteria. The current practice of the decision-making process does not consider all construction impacts in an integrated decision-making process. This dissertation developed a multi-criteria evaluation framework to support the decision-making process in highway construction projects. In addition to the construction cost and mobility impacts, reliability, safety, and emission impacts are assessed at different evaluation levels and used as inputs to the decision-making process. Two levels of analysis, referred to as the planning level and operation level, are proposed in this research to provide input to a Multi-Criteria Decision-Making (MCDM) process that considers user prioritization of the assessed criteria. The planning level analysis provides faster and less detailed assessments of the inputs to the MCDM utilizing analytical tools, mainly in a spreadsheet format. The second level of analysis produces more detailed inputs to the MCDM and utilizes a combination of mesoscopic simulation-based dynamic traffic assignment tool, and microscopic simulation tool, combined with other utilities. The outputs generated from the two levels of analysis are used as inputs to a decision-making process based on present worth analysis and the Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Situation) MCDM method and the results are compared.

碩士
國立高雄第一科技大學
國際管理碩士學位學程
100
ABSTRACT Supply chain management plays more and more important role in success of a manufacturing. Many practitioners and researchers have presented the advantages of supply chain management in literature. In order to increase the competitive advantage many companies consider that a well-designed and implemented supply chain system is an important role. Therefore, supplier selection problem becomes the most important issue to implement a successful supply chain system. This study proposes an extension of fuzzy multiple criteria decision-making (MCDM) model for the evaluation of supplier. Fuzzy MCDM is a powerful and widely-used tool for evaluating and ranking problems containing multiple criteria. In line with the multi-dimensional characteristics of supplier, fuzzy MCDM provides an effective framework for supplier comparison involving the evaluation of multiple criteria. Both qualitative and quantitative criteria and the different importance weights among criteria were considered in the model. The trade-off concept is used to evaluate the ratings of alternatives and importance weights of all the criteria. The membership functions of the final evaluation values were developed by using α-cuts. A revised method for ranking fuzzy numbers using maximizing set and minimizing set is applied to defuzzify all the final fuzzy evaluation values to allow the ordering of the alternatives. Finally, a numerical example is used to illustrate the feasibility and applicability of the proposed model. Keywords: Supply chain management, Supplier evaluation and selection, Fuzzy MCDM, Ranking method, Tradeoff concept.

碩士
開南大學
企業與創業管理學系
100
The research discusses competitive value, advantage sustained and appropriability which current businesses demand mostly to create competitive values based on resource-based view (RBV). In the previous studies discussing competitiveness based on RBV, no specific explanation for improvement was proposed. To improve the weakness, the study particularly adopts DEMATEL to establish a complete module framework to find out correlated factors for the success of a business, including the uniqueness, relatedness, sustainability, mobility, intellectual property rights and embeddedness. It also further calculates the influence of factors and sub-factor with ANP to compare the impact level and rank the priority of improvement for business. The result shows that an intellectual property right is the top priority, followed by relatedness, sustainability, mobility, uniqueness and embeddedness. Finally, VIKOR was used to rank the three similar Taiwanese businesses and prove that the module in the study is in accordance with practical business achievement. Also, Multiple Criteria Decision Making (MCDM) offers more enterprises the evaluation targets to create self-competitive values.

O Crédito Social potencia o desenvolvimento económico e social dos países. Todavia, atualmente, não existem muitos estudos que abordem esta temática, nomeadamente no que respeita à avaliação do risco de Crédito Social. Neste sentido, esta avaliação é frequentemente influenciada por fatores dispares que, em muitas circunstâncias, são mal compreendidos ou tratados de forma pouco clara e realista. Sustentando-se nos princípios da avaliação multicritério de apoio à tomada de decisão, bem como no uso integrado de técnicas de cartografia cognitiva com a metodologia TODIM – Tomada de Decisão Interativa Multicritério –, o presente estudo apresenta como principal objetivo a construção de um sistema idiossincrático de apoio à identificação de múltiplos critérios e ao cálculo dos respetivos ponderadores (i.e. tradeoffs), no âmbito da avaliação do risco de Crédito Social. Para o efeito, é seguida uma abordagem sociotécnica, materializada na realização de sessões presenciais com um grupo de especialistas em análise de crédito. Os resultados alcançados revelam que a combinação metodológica proposta permite acrescentar valor, fruto do contacto privilegiado com know-how especializado, aos processos de avaliação de pedidos de Crédito Social. As implicações práticas do estudo são também objeto de discussão
Social Credit enhances countries’ economic and social development. Currently, however, there are not many studies that address this issue, more specifically that focus on the assessment of Social Credit risk. This assessment is often influenced by different factors and, in many circumstances, is poorly understood or examined in an unrealistic way. Based on the principles of the multiple criteria decision analysis (MCDA), as well as on the integrated use of cognitive mapping and the TODIM methodology – Multicriteria Interactive Decision Making –, this study sought to develop an idiosyncratic decision support system for the identification of the underlying criteria, and calculation of the respective weights (i.e. trade-offs), in the risk assessment of Social Credit applications. As such, a sociotechnical approach is followed, grounded on face-to-face work sessions with an expert panel in credit risk analysis. The results show that the methodological combination presented in this study provides value to the evaluation processes of Social Credit applications, as a result of the privileged contact established with specialized knowhow. The practical implications of the study are also subject of discussion

博士
國立高雄科技大學
工業工程與管理系
107
Nowadays, the development of renewable energy sources is an urgent activity. Access to this type of renewable energy not only contributes to providing energy for society but also saves energy and reduces environmental pollution. In Vietnam, given the geographic conditions of a locality with long coastline, high winds and fairly distributed all the year, wind power plants emerged as a viable option. Thus, there are many wind power plants are building. One of the most importance aim of wind power projects is wind power plant location selection, wind farm location selection is Multi-Criteria Decision Making (MCDM) that the decision maker has to face. Although some studies have applied the MCDM model in wind farm location selection, very few studies have put attention on this fuzzy problem. That is why the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and hybrid Fuzzy Analytic Hierarchy Process (FAHP) are built for location selection of wind power farm in Vietnam. In the beginning, this study collected data from seven locations, with good conditions to invest in a wind power plant. an FAHP model was developed to determine the weight of each potential site to build a wind power farm. The TOPSIS is applied to rank all potential alternatives in the last stage. The results showed that Binh Thuan was the best place to build wind power plants in Vietnam. The contributions of this study has proposed an MCDM approach in a fuzzy environment for location selection of wind power farm in Vietnam. This article is also provide a practical approach and new flexible for a decision maker. This study can also provides a useful guide for wind farm locations selection in other countries.

博士
國立臺灣科技大學
工業管理系
102
Due to the importance and need of giving managers an overall tool for supporting the decision making process from a more general perspective, the present research introduces integrated multi-criteria approaches for decision making problems and applications. The aspect of this dissertation is to address two key studies. One of studies relates to the performance evaluation of the multiple manufacturing plants. This study develops an integrated approach that combines the voting method based on modified DEA and the fuzzy TOPSIS method to evaluate the performance of multiple manufacturing plants in a fuzzy environment. Fuzzy TOPSIS helps decision makers carry out analysis and comparisons in ranking their preference of the alternatives with vague or imprecise data. Since the evaluation result is often greatly affected by the weights used in the evaluation process, the voting method is used in this study to determine the appropriate criteria weights. The other study relates to the identification of key factors in improving the service quality of nursing homes. This study looks at improving the service quality in nursing homes as well as the intricate relationships between various factors. We use two research models herein. First, Interpretive Structural Modeling establishes the criteria for the inter-relationship structure, categorized according to their driving power and dependence. This methodology provides a means by which order can be imposed on the complexity of such criteria. Insights from this model can help top managers in strategic planning to improve the service quality in nursing home care. Second, because ISM does not provide any weighting associated with the criteria, we employ the Analytic Network Process approach to calculate the weighted importance of the key factors and to identify those factors impacting the service quality of nursing home care.

O crédito à habitação fortalece a economia dos países, contribuindo para o seu desenvolvimento e para o seu crescimento económico. Para que tal ocorra, porém, é necessário um compromisso financeiro entre a instituição de crédito que cede o montante e o indivíduo que o solicita. Essa relação é normalmente suportada por ferramentas de análise e avaliação de risco, que visam antecipar o sucesso ou o fracasso da cedência do crédito e proteger ambas as partes. Dada a crescente solicitação de sistemas de avaliação do risco de crédito mais realistas e informados, a presente dissertação visa a criação de um modelo multicritério de avaliação do risco de crédito à habitação com recurso a mapas cognitivos e à abordagem Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH). Apesar da natureza idiossincrática do estudo, os resultados revelam que esta opção metodológica permite a obtenção de sistemas de avaliação do risco de crédito mais transparentes e realistas. As vantagens e as limitações da proposta aqui apresentada são também objeto de análise e discussão.
Mortgage lending strengthens the economies of countries, contributing to their development and economic growth. For this to occur, a financial commitment is required between the credit institution that transfers the credit and the individual who requests it. This relationship is usually supported by risk analysis and assessment tools that aim to anticipate the success or failure of credit lending and protect both parties. Given the growing demand for more realistic and informed credit risk assessment mechanisms, the present study aims to create a multiple criteria credit risk assessment system for mortgage loans, using cognitive maps and the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH). Despite the idiosyncratic nature of the study, the results show that this methodological combination allows for more transparent and realistic credit risk assessment systems. The advantages and limitations of our proposal are also discussed.

碩士
中華大學
工業工程與管理研究所
88
In the past, we used Computer Simulation software to assist decision-maker to choose the best appropriate alternative for disposing of system problems. However, Computer Simulation software only used single criteria concept to generate the outcome. This rough estimation ignored the situation in the real world, and might come up with inappropriate result. Alternative evaluation should include characteristic of multiple criteria, but if we used only single criteria for decision-making, deviation might occur possibly. This deviation might lead to error and is unable to achieve expectant goal. This investigation is to associate Computer Simulation software and Multiple Criteria Decision-Making analysis, two analysis tools to design Multiple Criteria Decision-Making Supporter Programming (MCDMSP) individually, and use Taguchi method to dispose the experiment. Before using this program, we create case-study of hypothesis manufacturing system problems and explain analytical method to make use of process and result of executive. Compare it with single criteria decision-making analytical method moreover to find out the difference in the result and to explain its executing effects. Besides, proposing the structure of Multiple Criteria Decision-Making analysis to adopt in Computer Simulation software alternative evaluation. Understanding the usage and effectiveness of the Computer Simulation software supplementary function program will help us to know this new contemplation direction and to choose the best appropriate alternative for disposing of system problems.

博士
中原大學
企業管理研究所
105
With the gradual improvement of the socialist market economy system in China, increasingly more enterprises are introducing modern enterprise systems to meet the needs of emerging markets. One of the most substantial paradigm shifts of modern business management is that individual manufacturers no longer compete as solely autonomous entities, but rather as internetwork competition. Therefore, new concepts of supply chain management (SCM) are arising. Global environmental issues have attracted increasing public attention in recent years. As one of the most crucial industries in China, the automotive industry should focus on green SCM, and consequently, environmental factors for supplier selection should be considered. In addition, as a crucial part of producer services, the logistics industry is highly dependent on the manufacturing industry. In general, the interactive development of logistics and manufacturing industries is essential; in particular, it is a key to improving core competitiveness and promoting ongoing improvement among manufacturing firms. Supply chain management is a classic case of multiple criteria decision-making (MCDM). The decision-making trial and evaluation laboratory–based analytic network process (DANP) has played a paramount role in identifying key factors and causal relationships. However, the DANP usually requires pairwise comparison questionnaire surveys. Respondents may be unwilling to fill out a large number of questionnaire items; this can interfere with the final outcome analysis and limits the application of the DANP and the use of secondary data. Therefore, this dissertation proposes a novel MCDM model combining grey relational analysis and the DANP, namely the GDANP. The GDANP can measure influence relationships and causal relationships through Delphi surveys and secondary data. To highlight the application and development potential of the GDANP in SCM, it was applied in two real-world cases. Case 1 identified key factors affecting Chinese automotive manufacturers in their green parts’ supplier selection by Delphi questionnaires. The results showed that the key factors are cost, quality, technology, and pollution control, respectively, in supplier selection. They also showed that Chinese automotive manufacturers consider economic factors to be much more important than environmental factors and gradually attach greater importance to green management by emphasising pollution control. In Case 2, statistical data for logistics and manufacturing industries in the China Statistical Yearbook (2006–2015) were used to identify the key factors for interaction between these two industries. The results showed that the key logistics criteria for interaction development are the total number of employees in the transport business, volume of goods, and total length of routes. The key manufacturing criteria for interaction development are gross domestic product and value added. Therefore, stakeholders should increase the number of employees in the transport industry and freight volumes. Also, the investment in infrastructure should be increased. Based on the practical results, the GDANP has two clear advantages over the traditional methods. 1. The GDANP allows the use of historical statistical data as input, rather than respondent questionnaires, which enables the GDANP to achieve superior results with secondary data. Because negative performance values can also be analyzed in the GDANP, it is more flexible than the traditional entropy method. 2. The GDANP can automatically generate comparison matrices of pairwise influence, greatly reducing computational complexity and obviating the requirement for respondents to fill out numerous items derived from a tedious comparison matrix of pairwise influence. The results obtained by the GDANP are consistent with expert opinions, which highlights the effectiveness and excellent development potential of the proposed method in the practice of SCM.

碩士
國立虎尾科技大學
工業工程與管理研究所
99
Gartner reported that worldwide mobile device sales to end users reached 1.6 billion units in 2010; smart phone sales grew 72 percent in 2010, and accounted for 19 percent of total mobile communications device sales in 2010. Strong smart phone sales in the fourth quarter of 2010 pushed Apple and Research In Motion (RIM) up in our 2010 worldwide ranking of mobile device manufacturers to the No. 5 and No. 4 positions, respectively, displacing SonyEricsson and Motorola. This means the smart phone market is soaring. All suppliers pour into high value-added smart phone market, and the market is expected to gain higher revenue and profits. However, most new products are unable to survive in market; especially the technological products like smart phones. The one of reasons is that suppliers take the preferences of engineers instead of consumers’ preferences. The objective of this research is to investigate the consumers’ preferences of function attributes of smart phones. The questionnaires were first given to the experts/sales in the cell phone shops to collect the relatively important function attributes. Then, Analytical Hierarchy Process (AHP) questionnaires were given to the smart phone users, and the data is used to derive the weight of function attributes. Finally, Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)、Grey Relational Analysis(GRA) were used to select the best choice of smart phones. The results of the research showed: 1. There are 15 important function attributes picked up by experts/sales in the cell phone shops. 2. After the AHP, the top five function attributes are application software, global positioning system (GPS), user interface, Internet connectivity, and games. 3. Based on the weight of function attributes, SonyEricsson is selected by using TOPSIS and GRA. However, iPhone is the best seller in the smart phone market right now; thus, it may indicate that the function attributes are not the only decision factor of consumer to select a smart phone.

碩士
朝陽科技大學
企業管理系
105
The purpose of this study is to evaluate and develop a model of marketing audit (MA) implementation criteria. This study appears to be one of the first papers to focus on the use and contribution of analytic hierarchy process (AHP) on the marketing audit implementation criteria. Based on ten practical marketing experts’ opinions and evaluations from Taiwan, we conducted an AHP decision model for assessing the priority of marketing audits criteria for Taiwan’s small and medium enterprises (SMEs). Our study consists of two phases. In the first phase, we investigate the potential criteria of marketing audits implementation from literature. Then, in the second phase, we created an AHP model to determine the relative priorities of auditing criteria by accommodating both the objective and subjective judgments of the ten practical experts participating in this study. Our result indicates that the marketing strategy related standards and auditing criteria appear to be the top priority while implementing MA and the following are the marketing environment audit, marketing productivity audit, marketing system audit, marketing organization audit, and marketing function audit. In addition, from the perspective of cause-effect relationship, the marketing environments, organization, strategy audits appear to be the causes of the marketing system, function and productivity audits. This study also proposes some suggestions for the decision making of practical hierarchical marketing audit criteria. A comparative analysis of results by VIKOR method and survey method used in 2010 showed that the both priorities of implementing marketing audit dimensions are similar, and marketing strategy audit, marketing environment audit and marketing productivity audit contribute firms greater than the other dimensions.

The business cycle in the automotive industry follows the general economic cycle closely and therefore, undergoes cyclical fluctuations over time. Companies in the sector are faced with challenges and need to deal with market demands efficiently and quickly to stay competitive. Lean approach is one of the strategies that can aid firms to improve their competitiveness by minimizing waste (Pullan et al., 2013). In order to benefit from a lean approach, the first step is to select a proper tool based on the available resources and requirements of the company. Due to the fact that numerous lean tools have been introduced over time, decision makers in company may encounter challenges in selecting the proper one with regard to their demands. To deal with such an issue, Multi-Criteria Decision-Making (MCDM) can greatly assist decision makers to compare available alternatives and consequently select the best possible solution among them. This study aims at improving the operational process in MCoutinho Group, a Portuguese well-known company in the automotive sector, by helping the management board in selecting lean tool due to the company preferences. In this study, the applicability (and results) of the application of some MCDM techniques (SAW, TOPSIS, and VIKOR) is examined to compare ten lean tools, determined based on the literature. The results reveal some gaps between company requirements and the demands which have been considered in previous surveys. The process applied can save the costs of trial and error of implementing different lean tools. And finally, adopting such a lean tool that has been selected totally based on the exclusive requirements of the company can improve efficiency in the company.
O ciclo de negócios na indústria automotiva segue de perto o ciclo econômico geral e, portanto, sofre flutuações cíclicas ao longo do tempo. As empresas do setor enfrentam desafios e precisam lidar com as demandas do mercado de forma eficiente e rápida para se manterem competitivas. A abordagem enxuta é uma das estratégias que pode ajudar as empresas a melhorar sua competitividade, minimizando o desperdício (Pullan et al., 2013). Para se beneficiar de uma abordagem enxuta, o primeiro passo é selecionar uma ferramenta adequada com base nos recursos disponíveis e requisitos da empresa. Devido ao fato de que várias ferramentas enxutas foram introduzidas ao longo do tempo, os tomadores de decisão na empresa podem encontrar desafios ao selecionar a ferramenta adequada com relação às suas demandas. Para lidar com essa questão, a Tomada de Decisão Multi-Critérios (MCDM) pode ajudar muito os tomadores de decisão a comparar as alternativas disponíveis e, conseqüentemente, selecionar a melhor solução possível entre elas. Este estudo tem como objetivo melhorar o processo operacional do Grupo MCoutinho, empresa portuguesa de renome no setor automóvel, auxiliando a administração na seleção da ferramenta enxuta em função das preferências da empresa. Neste estudo, a aplicabilidade (e resultados) da aplicação de algumas técnicas MCDM (SAW, TOPSIS e VIKOR) é examinada para comparar dez ferramentas enxutas, determinadas com base na literatura. Os resultados revelam algumas lacunas entre os requisitos da empresa e as demandas consideradas em pesquisas anteriores. O processo aplicado pode economizar os custos de tentativa e erro de implementação de diferentes ferramentas enxutas. E, por fim, a adoção de uma ferramenta tão enxuta que foi selecionada totalmente com base nos requisitos exclusivos da empresa pode melhorar a eficiência da empresa.

With the fast-growing of data-rich systems, dealing with complex decision problems is unavoidable. Normalization is a crucial step in most multi criteria decision making (MCDM) models, to produce comparable and dimensionless data from heterogeneous data. Further, MCDM requires data to be numerical and comparable to be aggregated into a single score per alternative, thus providing their ranking. Several normalization techniques are available, but their performance depends on a number of characteristics of the problem at hand i.e., different normalization techniques may provide different rankings for alternatives. Therefore, it is a challenge to select a suitable normalization technique to represent an appropriate mapping from source data to a common scale. There are some attempts in the literature to address the subject of normalization in MCDM, but there is still a lack of assessment frameworks for evaluating normalization techniques. Hence, the main contribution and objective of this study is to develop an assessment framework for analysing the effects of normalization techniques on ranking of alternatives in MCDM methods and recommend the most appropriate technique for specific decision problems. The proposed assessment framework consists of four steps: (i) determining data types; (ii) chose potential candidate normalization techniques; (iii) analysis and evaluation of techniques; and (iv) selection of the best normalization technique. To validate the efficiency and robustness of the proposed framework, six normalization techniques (Max, Max-Min, Sum, Vector, Logarithmic, and Fuzzification) are selected from linear, semi-linear, and non-linear categories, and tested with four well known MCDM methods (TOPSIS, SAW, AHP, and ELECTRE), from scoring, comparative, and ranking methods. Designing the proposed assessment framework led to a conceptual model allowing an automatic decision-making process, besides recommending the most appropriate normalization technique for MCDM problems. Furthermore, the role of normalization techniques for dynamic multi criteria decision making (DMCDM) in collaborative networks is explored, specifically related to problems of selection of suppliers, business partners, resources, etc. To validate and test the utility and applicability of the assessment framework, a number of case studies are discussed and benchmarking and testimonies from experts are used. Also, an evaluation by the research community of the work developed is presented. The validation process demonstrated that the proposed assessment framework increases the accuracy of results in MCDM decision problems.
Com o rápido crescimento dos sistemas ricos em dados, lidar com problemas de decisão complexos é inevitável. A normalização é uma etapa crucial na maioria dos modelos de tomada de decisão multicritério (MCDM), para produzir dados comparáveis e adimensionais a partir de dados heterogéneos, porque os dados precisam ser numéricos e comparáveis para serem agregados em uma única pontuação por alternativa. Como tal, várias técnicas de normalização estão disponíveis, mas o seu desempenho depende de uma série de características do problema em questão, ou seja, diferentes técnicas de normalização podem resultar em diferentes classificações para as alternativas. Portanto, é um desafio selecionar uma técnica de normalização adequada para representar o mapeamento dos dados de origem para uma escala comum. Existem algumas tentativas na literatura de abordar o assunto da normalização, mas ainda há uma falta de estrutura de avaliação para avaliar as técnicas de normalização sobre qual técnica é mais apropriada para os métodos MCDM.Assim, a principal contribuição e objetivo deste estudo são desenvolver uma ferramenta de avaliação para analisar os efeitos das técnicas de normalização na seriação de alternativas em métodos MCDM e recomendar a técnica mais adequada para problemas de decisão específicos. A estrutura de avaliação da ferramenta proposta consiste em quatro etapas: (i) determinar os tipos de dados, (ii) selecionar potenciais técnicas de normalização, (iii) análise e avaliação de técnicas em problemas de MCDM, e (iv) recomendação da melhor técnica para o problema de decisão. Para validar a eficácia e robustez da ferramenta proposta, seis técnicas de normalização (Max, Max-Min, Sum, Vector, Logarithmic e Fuzzification) foram selecionadas - das categorias lineares, semilineares e não lineares- e quatro conhecidos métodos de MCDM foram escolhidos (TOPSIS, SAW, AHP e ELECTRE). O desenho da ferramenta de avaliação proposta levou ao modelo conceptual que forneceu um processo automático de tomada de decisão, além de recomendar a técnica de normalização mais adequada para problemas de decisão. Além disso, é explorado o papel das técnicas de normalização para tomada de decisão multicritério dinâmica (DMCDM) em redes colaborativas, especificamente relacionadas com problemas de seleção de fornecedores, parceiros de negócios, recursos, etc. Para validar e testar a utilidade e aplicabilidade da ferramenta de avaliação, uma série de casos de estudo são discutidos e benchmarking e testemunhos de especialistas são usados. Além disso, uma avaliação do trabalho desenvolvido pela comunidade de investigação também é apresentada. Esta validação demonstrou que a ferramenta proposta aumenta a precisão dos resultados em problemas de decisão multicritério.