Relevant bibliographies by topics / Multi-criteria Decision Making (MCDM) techniques

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Academic literature on the topic 'Multi-criteria Decision Making (MCDM) techniques'

Author: Grafiati
Published: 19 February 2023

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Journal articles on the topic "Multi-criteria Decision Making (MCDM) techniques"

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Azhar, Nayli Adriana, Nurul Asyikin Mohamed Radzi, and Wan Siti Halimatul Munirah Wan Ahmad. "Multi-criteria Decision Making: A Systematic Review." (Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 14, no. 8 (December 23, 2021): 779–801. http://dx.doi.org/10.2174/2352096514666211029112443.

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Multi Criteria Decision Making (MCDM) helps decision makers (DMs) solve highly complex problems. Accordingly, MCDM has been widely used by DMs from various fields as an effective and reliable tool for solving various problems, such as in site and supplier selection, ranking and assessment. This work presents an in-depth survey of past and recent MCDM techniques cited in the literature. These techniques are mainly categorised into pairwise comparison, outranking and distance-based approaches. Some well-known MCDM methods include the Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), Elimination et Choix Traduisant la Realité (ELECTRE), Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Each of these methods is unique and has been used in a vast field of interest to support DMs in solving complex problems. For a complete survey, discussions related to previous issues and challenges and the current implementation of MCDM are also presented.
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Massam, Bryan H. "Multi-Criteria Decision Making (MCDM) techniques in planning." Progress in Planning 30 (January 1988): 1–84. http://dx.doi.org/10.1016/0305-9006(88)90012-8.

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Abdulaal, Reda M. S., and Omer A. Bafail. "Two New Approaches (RAMS-RATMI) in Multi-Criteria Decision-Making Tactics." Journal of Mathematics 2022 (September 27, 2022): 1–20. http://dx.doi.org/10.1155/2022/6725318.

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When a decision must be made, a tool called multi-criteria decision-making (MCDM) is used to assess and select alternatives among numerous criteria. For a wide variety of complex problems, MCDM methods have demonstrated usefulness in finding the optimal solutions. Despite the abundance of MCDM methods available today, there has been slow progress in developing new methodologies in MCDM in the past decade. In this context, this paper presents new MCDM tools which ranks alternatives based on median similarity (RAMS) between optimal alternatives and other alternatives. RAMS is an extension to the most recently developed technique that used perimeter similarity (RAPS). This paper also introduces a further tool that combines the RAMS method with the multiple criteria ranking by alternative trace (MCRAT) methodology using a majority index and the concept of the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. This tool is ranking the alternatives based on the trace to median index (RATMI). An illustration of the use of RAMS and RATMI is given through a case study of ranking different materials for the selection of break booster valve body in a vehicle. The validity of the new two techniques was tested against seven well-known MCDM techniques (ARAS, SAW, TOPSIS, COPRAS, VIKOR, WASPAS, and MOORA) using fifteen real problems data taken from the literature. The RATMI technique was more promising than RAPS and RAMS for 87% and 93% of the fifteen difficulties, respectively, according to the results of the correlation coefficient tests between the developed techniques and the selected seven techniques.
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Yang, Zhe, Kan Yang, Yufeng Wang, Lyuwen Su, and Hu Hu. "The improved multi-criteria decision-making model for multi-objective operation in a complex reservoir system." Journal of Hydroinformatics 21, no. 5 (June 21, 2019): 851–74. http://dx.doi.org/10.2166/hydro.2019.150.

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Abstract In multi-objective reservoir operation, it is vital for decision-makers to select optimal scheduling schemes through efficient multi-criteria decision-making (MCDM) techniques. However, in the family of MCDM methods, it is difficult for the technique for order preference by similarity to an ideal solution (TOPSIS) to describe grey correlation, thus making decisions with less reliability. To this end, a framework supporting high-quality solutions' acquirement and optimal reservoir operation decision-making is established. The improved multi-objective particle swarm optimization (IMOPSO), a new efficient MCDM model based on TOPSIS and grey correlation analysis (GCA), and combination weighting method based on the minimum deviation (CWMMD) are included in the framework. The non-inferior solution set is efficiently obtained by IMOPSO and optimal decision information is provided for decision-makers using the MCDM model. Moreover, the CWMMD is used to determine weighting information of multiple evaluation indicators. Numerical simulations are conducted to verify the efficiency of the proposed methodology and support decision-making for multi-objective reservoir operation in Hongjiadu and Qingjiang basins. The results indicate that the proposed methodology can provide non-inferior scheduling solutions and decision-making instruction with higher reliability for multi-objective reservoir operation.
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García, Vicente, J. Salvador Sánchez, and Ana I. Marqués. "Synergetic Application of Multi-Criteria Decision-Making Models to Credit Granting Decision Problems." Applied Sciences 9, no. 23 (November 22, 2019): 5052. http://dx.doi.org/10.3390/app9235052.

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Although various algorithms have widely been studied for bankruptcy and credit risk prediction, conclusions regarding the best performing method are divergent when using different performance assessment metrics. As a solution to this problem, the present paper suggests the employment of two well-known multiple-criteria decision-making (MCDM) techniques by integrating their preference scores, which can constitute a valuable tool for decision-makers and analysts to choose the prediction model(s) more properly. Thus, selection of the most suitable algorithm will be designed as an MCDM problem that consists of a finite number of performance metrics (criteria) and a finite number of classifiers (alternatives). An experimental study will be performed to provide a more comprehensive assessment regarding the behavior of ten classifiers over credit data evaluated with seven different measures, whereas the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE) techniques will be applied to rank the classifiers. The results demonstrate that evaluating the performance with a unique measure may lead to wrong conclusions, while the MCDM methods may give rise to a more consistent analysis. Furthermore, the use of MCDM methods allows the analysts to weight the significance of each performance metric based on the intrinsic characteristics of a given credit granting decision problem.
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Francik, Sławomir, Norbert Pedryc, Adrian Knapczyk, Artur Wójcik, Renata Francik, and Bogusława Łapczyńska-Kordon. "Bibliometric analysis of multiple criteria decision making in agriculture." Technical Sciences 1, no. 20 (December 15, 2016): 17–30. http://dx.doi.org/10.31648/ts.2906.

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Development trends (Research Trends) in scientific research on the methods of Multiple Criteria Decision Making (MCDM) and Multiple Criteria Decision Analysis (MCDA) in agriculture are analyzed. Established bibliometric techniques are applied. MCDA/MCDM methods are being very intensively developed in recent years, as evidenced by the number of scientific papers published annually in renowned scientific journals indexed in the Web of Science (WoS) database. In the years 1979-2015 a total of 1,355 scientific articles were collected in the database. The number of articles published annually increased rapidly after 2005. Besides, the annual number of citations of the publications is increasing. Research on MCDA/MCDM is conducted in many research areas. In the years 1984-2015 the Web of Science database accumulated 27 scientific publications on MCDA/MCDM in agriculture area. Therefore, it can be concluded that the MCDA/MCDM issues are currently not sufficiently analyzed in relation to agriculture. In the future this subject will probably be further developed, an increasing number of scientists will conduct research on the MCDA/MCDM and the annual number of articles published in the field will increase.
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Sikder, Abu Hena Mustafa Kamal, and Mashfiqus Salehin. "Multi-criteria decision making methods for rural water supply: a case study from Bangladesh." Water Policy 17, no. 6 (June 3, 2015): 1209–23. http://dx.doi.org/10.2166/wp.2015.111.

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Multiple criteria decision making (MCDM) is a process of evaluating alternatives against relevant decision making criteria. Several methods are available to facilitate the evaluation steps. This paper deals with a rural water supply problem in the coastal areas of Bangladesh. Three different MCDM methods – weighted summation, analytical hierarchy process, and novel approach to imprecise assessment and decision environments – were used to evaluate the suitable water supply alternative. The ranking of alternatives obtained from these MCDM techniques produced similar results. Among five water supply alternatives evaluated, rainwater harvesting systems and deep tube wells scored first and second, respectively, for all three evaluation methods. In addition, sensitivity analyses were carried out for the MCDM techniques and these results did not show drastic variations either. This finding implies that while selection of MCDM technique is important, when evaluating similar problems more emphasis should be given to defining the problem comprehensively and thus selecting the relevant criteria and priorities to factor into the decision problem.
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Zavadskas, Edmundas Kazimieras, Dragan Pamučar, Željko Stević, and Abbas Mardani. "Multi-Criteria Decision-Making Techniques for Improvement Sustainability Engineering Processes." Symmetry 12, no. 6 (June 9, 2020): 986. http://dx.doi.org/10.3390/sym12060986.

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The success of any activity and process depends fundamentally on the possibility of balancing (symmetry) needs and their satisfaction. That is, the ability to properly define a set of success indicators. The application of the developed new multi-criteria decision-making (MCDM) methods can be eliminated or decreased by decision-makers’ subjectivity, which leads to consistency or symmetry in the weight values of the criteria. In this Special Issue, 40 research papers and one review study co-authored by 137 researchers from 23 different countries explore aspects of multi-criteria modeling and optimization in crisp or uncertain environments. The papers proposing new approaches and elaborate case studies in the following areas of applications: MCDM optimization in sustainable engineering, environmental sustainability in engineering processes, sustainable multi-criteria production and logistics processes planning, integrated approach for modeling processes in engineering, new trends in the multi-criteria evaluation of sustainable processes, multi-criteria decision-making in strategic management based on sustainable criteria.
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Alyazji, Qasem Anwar, and Gulsum Asiksoy. "Evaluating Mechanical Ventilators Using Multi Criteria Decision Making Techniques." International Journal of Online and Biomedical Engineering (iJOE) 17, no. 07 (July 2, 2021): 4. http://dx.doi.org/10.3991/ijoe.v17i07.21769.

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Mechanical ventilator (MV) is used to help the patient breathe by delivering gas to the lungs at a certain rate using positive pressure. The complex evaluation of mechanical ventilator devices at present time is a very important and topical issue, due to the presence of many mechanical ventilator companies, as it seems that the process of evaluation and selection of ventilator equipment needs strong experience in this field. Our paper show that multi criteria decision making (MCDM) methods can be applied to comparing and evaluating some alternatives of mechanical ventilator devices. This study will determine new methodology to help the decision makers to choosing the best mechanical ventilator among the five alternatives based on eight criteria; Cost of the MV device; Maximum Inspiratory flow; Maximum Pressure; Tidal volume; PEEP; Weight of ventilator; Screen size and Internal battery time. This study used two techniques; TOPSIS technique and PROMETHEE II technique. Our paper used the same weights criteria in these two techniques. The weight for each criteria should be determined by the medical engineer expert and the decision makers. Choosing mechanical ventilator will affect the quality of the therapeutic and diagnostic processes, the way the treating doctor works, and also affect the patient's comfort. Because of these reasons, we designed a new methodology based on MCDM. This study will be an important basis for choosing the best mechanical ventilator, and will assist decision-makers such as medical engineers, ICU doctors, and users to evaluating and choosing the best ventilator based on several criteria.
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Balogun, A. O., A. O. Bajeh, H. A. Mojeed, and A. G. Akintola. "Software defect prediction: A multi-criteria decision-making approach." Nigerian Journal of Technological Research 15, no. 1 (April 30, 2020): 35–42. http://dx.doi.org/10.4314/njtr.v15i1.7.

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Failure of software systems as a result of software testing is very much rampant as modern software systems are large and complex. Software testing which is an integral part of the software development life cycle (SDLC), consumes both human and capital resources. As such, software defect prediction (SDP) mechanisms are deployed to strengthen the software testing phase in SDLC by predicting defect prone modules or components in software systems. Machine learning models are used for developing the SDP models with great successes achieved. Moreover, some studies have highlighted that a combination of machine learning models as a form of an ensemble is better than single SDP models in terms of prediction accuracy. However, the efficiency of machine learning models can change with diverse predictive evaluation metrics. Thus, more studies are needed to establish the effectiveness of ensemble SDP models over single SDP models. This study proposes the deployment of Multi-Criteria Decision Method (MCDM) techniques to rank machine learning models. Analytic Network Process (ANP) and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) which are types of MCDM techniques are deployed on 9 machine learning models with 11 performance evaluation metrics and 11 software defects datasets. The experimental results showed that ensemble SDP models are best appropriate SDP models as Boosted SMO and Boosted PART ranked highest for each of the MCDM techniques. Besides, the experimental results also validated the stand of not considering accuracy as the only performance evaluation metrics for SDP models. Conclusively, more performance metrics other than predictive accuracy should be considered when ranking and evaluating machine learning models. Keywords: Ensemble; Multi-Criteria Decision Method; Software Defect Prediction
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Dissertations / Theses on the topic "Multi-criteria Decision Making (MCDM) techniques"

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Landmesser, John Andrew. "Improving it portfolio management decision confidence using multi-criteria decision making and hypervariate display techniques." Thesis, Nova Southeastern University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3609737.

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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.

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Saksrisathaporn, Krittiya. "A multi-criteria decision support system using knowledge management and project life cycle approach : application to humanitarian supply chain management." Thesis, Lyon 2, 2015. http://www.theses.fr/2015LYO22016/document.

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Cette thèse vise à contribuer à la compréhension des cycle de vie d’une opération humanitaire (HOLC). Gestion de la chaîne d'approvisionnement humanitaire (HSCM) dans un contexte de mise en perspective et dans l’objectif de proposer un modèle décisionnel qui s'applique aux phases de HOLC lors d’une situation réelle. Cela inclut la mise en oeuvre du modèle proposé pour concevoir et développer un outil d'aide à la décision afin d'améliorer les performances de la logistique humanitaire tant dans les opérations de secours nationaux qu’internationaux.Cette recherche est divisée en trois phases. La première partie vise à présenter le sens de l'étude ; la zone de recherche prise en compte pour la gestion de la chaîne d'approvisionnement (SCM) doit être clairement définie. La première phase consiste à clarifier et définir le HSCM HL, la gestion de la chaîne d'approvisionnement commerciale (CSCM) et le SCM, ainsi que la relation entre ces différents éléments. La gestion du cycle de vie du projet (PLCM) et les différentes approches sont également présentés. La compréhension de la différence entre la gestion du cycle de vie du projet (PLM) et la PLCM est également nécessaire, cela ne peut être abordé dans la phase de cycle de vie de l'opération humanitaire. De plus, les modèles Multiple-Criteria Decision Making (MCDM) et l’aide à la décision concernant le HL sont analysés pour établir le fossé existant en matière de recherche. Les approches MCDM qui mettent en oeuvre le système d'aide à la décision (DSS) et la manière dont le MAS a été utilisé dans le contexte HSCM sont étudiées.La deuxième phase consiste en la proposition d’un modèle décisionnel fondé sur l’approche MCDM à l'appui de la décision du décideur avant qu'il/elle prenne des mesures. Ce modèle prévoit le classement des alternatives concernant l'entrepôt, le fournisseur et le transport au cours des phases de HOLC. Le modèle décisionnel proposé est réalisée en 3 scénarios. I. La décision en 4phases HOLC – opération de secours internationale de la Croix-Rouge Française (CRF). II. La décision en3phases HOLC – opération nationale dela Croix-Rouge thaïlandaise (TRC). III. La décision au niveau de la phase de réponse HOLC – opération internationale du TRC dans quatre pays. Dans cette phase, le scénario I et II sont réalisés étape par étape au travers de calculs numériques et formules mathématiques. Le scénario III sera présenté dans la troisième phase. Pour établir trois scénarios, les données internes recueillies lors des entretiens avec le chef de la logistique de la Croix-Rouge Française, et le vice-président de la fondation de la Coix-Rouge thaïlandaise, seront utilisées. Les données externes proviennent de chercheurs qui sont des experts dans le domaine HL ou le champ du HSCM, de la littérature, et de sources issues des organismes humanitaires (documents d’ateliers, rapports, informations publiées sur leurs sites officiels).Dans la troisième phase, une application Internet multi-critères (decision support system MCDSS WB) mettant en oeuvre le modèle proposé est élaborée. Afin d'atteindre une décision appropriée en temps réel, le WB-MCDSS est développé sur la base d’un protocole client-serveur et est simple à utiliser. Le dernier mais non le moindre ; une application de validation du modèle est réalisée à l'aide de l'approche de l'analyse de sensibilité
This thesis aims to contribute to the understanding of HOLC in context of the HSCM and to propose a decision model which applies to the phases of HOLC the decision making regarding a real situation . This include the implementation of the proposed model to design and develop a decision support tool in order to improve the performance of humanitarian logistics in both national and international relief operations.This research is divided into three phases; the first phase is to clarify and define HL among HSCM, commercial supply chain management (CSCM) and SCM and their relationship. Project Life Cycle Management (PLCM) approaches are also presented. The difference between project life cycle management (PLM) and PLCM is also required to distinguish a clear understanding which can be addressed in the phase of humanitarian operation life cycle. Additionally, the literature of Multiple-Criteria Decision Making (MCDM) models and existing decision aid system for HL are analyzed to establish the research gap. The MCDM approaches which implement the decision support system (DSS) and lastly how DSS has been used in the HSCM context.The second phase is to propose a decision model based on MCDM approaches to support the decision of the decision maker before he/she takes action. This model provides the ranking alternatives to warehouse, supplier and transportation over the phases of HOLC. The proposed decision model is conducted in 3 scenarios; I. The decision in 4-phase HOLC, international relief operation of French Red Cross (FRC). II. The decision on 3-phase HOLC, national operation by the Thai Red Cross (TRC). III. The decision on response phase HOLC, international operation by the FRC in four countries. In this phase, the scenario I and II are performed step by step though numerical calculation and mathematical formulas. The scenario III will be presented in the third phase.In the third phase, an application of web-based multi-criteria decision support system (WB-MCDSS) which implement the proposed model is developed. The web-based multi-criteria decision support system is developed based on the integration of analytical hierarchy process (AHP) and TOPSIS approaches. In order to achieve an appropriate decision in a real time response, the WB-MCDSS is developed based on server-client protocol and is simple to operate. Last but not least, a validation application of the model is performed using the sensitivity analysis approach
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Medineckiene, Milena. "Integrated decision making in civil engineering, based on multi-criteria assessment and buildings’ certification." Doctoral thesis, KTH, Byggnadsteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-200946.

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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
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Mehmood, Tallat, and Farnaz Khodabandeh. "Ranking suppliers by using the Sustainable Supplier Evaluation Criteria (SSEC) and Multi-Criteria Decision Making (MCDM) methods." Thesis, Linnéuniversitetet, Institutionen för ekonomistyrning och logistik (ELO), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-64703.

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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.
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jia, jianmin. "Multi-Criteria Evaluation in Support of the Decision-Making Process in Highway Construction Projects." FIU Digital Commons, 2017. http://digitalcommons.fiu.edu/etd/3202.

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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.
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Dunn, Alexander Hiram. "A multi-criteria approach to the evaluation of food safety interventions." Thesis, University of Canterbury. Management, Marketing and Entrepreneurship, 2015. http://hdl.handle.net/10092/10243.

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New Zealand faces a range of food safety hazards. Microbial hazards alone were estimated to cause over 2,000 years of lost healthy life in 2011 (Cressey, 2012) and $62m in medical costs and lost productivity in 2009 (Gadiel & Abelson, 2010). Chemical hazards are thought to be well managed through existing controls (Vannoort & Thomson, 2009) whereas microbial hazards are considered harder to control, primarily due to their ability to reproduce along the food production chain. Microbial hazards are thought to cause the majority of acute foodborne gastroenteritis. This research reviewed food safety literature and official documentation, and conducted 55 interviews, mostly with food safety experts from different stakeholder groups, to examine the food safety decision-making environment in New Zealand. This research explores the concept of the ‘stakeholder’ in the context of food safety decision-making and proposes an inclusive ‘stakeholder’ definition as any group which is able to affect, or be affected by, the decision-making process. Utilising this definition, and guided by interviews, New Zealand stakeholders in food safety decision-making were identified and classified as follows: •Regulators •Public health authorities •Food safety scientists/academics •Consumers •Māori •Food Businesses (further classified as): o Farmers o Processors o Food retailers o Exporters Interviews with stakeholders from these groups highlighted twelve criteria as being relevant to multiple groups during food safety intervention evaluation: •Effectiveness •Financial cost •Market Access •Consumer Perceptions •Ease of Implementation •Quality or Suitability •Quality of Science •Equity of Costs •Equity of Benefits •Workplace Safety •Cultural Impact •Animal Welfare There are a number of different ways to measure or assess performance on these criteria. Some are able to be quantitatively measured, while others may require the use of value judgements. This thesis used the Disability-Adjusted Life Year (DALY) metric for quantifying effectiveness during the testing of different MCDA models. This thesis reviews the MCDA process and the food safety specific MCDA literature. There are different ways of conducting MCDA. In particular, there are a large number of models available for the aggregation phase; the process of converting model inputs, in the form of criteria scores and weights, into model recommendations. This thesis has described and reviewed the main classes of model. The literature review and interview process guided the construction and testing of three classes of MCDA model; the Weighted Sum, Analytic Hierarchy Process (AHP) and PROMETHEE models. These models were selected due to their having different characteristics and degrees of complexity, as well as their popularity in the food safety and Health Technology Assessment (HTA) literature. Models were tested on the problem of selecting the most appropriate intervention to address the historic Campylobacter in poultry problem in New Zealand during the mid-2000s. Experimentation was conducted on these models to explore how different configurations utilise data and produce model outputs. This experimentation included: •Varying the format of input data •Exploring the effects of including/excluding criteria •Methods for sensitivity analysis •Exploring how data inputs and outputs can be elicited and presented using visual tools • Creating and using hybrid MCDA models The results of this testing are a key output of this thesis and provide insight into how such models might be used in food safety decision-making. The conclusions reached throughout this research phase can be classified into one of two broad groups: •Those relating to MCDA as a holistic process/methodology for decision-making •Those relating to the specific models and mathematical procedures for generating numerical inputs and outputs This thesis demonstrates that food-safety decision-making is a true multi-criteria, multi-stakeholder problem. The different stakeholders in food-safety decision-making do not always agree on the value and importance of the attributes used to evaluate competing intervention schemes. MCDA is well suited to cope with such complexity as it provides a structured methodology for the systematic and explicit identification, recording and aggregation of qualitative and quantitative information, gathered from a number of different sources, with the output able to serve as a basis for decision-making. The MCDA models studied in this thesis range from models that are simple and quick to construct and use, to more time consuming models with sophisticated algorithms. The type of model used for MCDA, the way these models are configured and the way inputs are generated or elicited can have a significant impact on the results of an analysis. This thesis has identified a number of key methodological considerations for those looking to employ one of the many available MCDA models. These considerations include: •Whether a model can accommodate the type and format of input data •The desired degree of compensation between criteria (i.e. full, partial or no compensation) •Whether the goal of an analysis is the identification of a ‘best’ option(s), or the facilitation of discussion, and communication of data •The degree of transparency required from a model and whether an easily understood audit trail is desired/required •The desired output of a model (e.g. complete or partial ranking). This thesis has also identified a number of practical considerations when selecting which model to use in food safety decision-making. These include: •The amount of time and energy required of stakeholders in the generation of data inputs (elicitation burden) •The degree of training required for participants •How data inputs are to be elicited and aggregated in different group decision-making environments •The availability of MCDA software for assisting an analysis Considering the above points will assist users in selecting a suitable MCDA model that meets their requirements and constraints. This thesis provides original and practical knowledge to assist groups or individuals looking to employ MCDA in the context of food-safety intervention decision-making. This research could also serve as a guide for those looking to evaluate a different selection of MCDA models.
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Tiesmeier, Dominique Katlin. "MCDM problem-structuring framework and a real estate decision support model." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/mcdm-problemstructuring-framework-and-a-real-estate-decision-support-model(a3376b20-6d3c-4b78-9aac-e645b454ad51).html.

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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.
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Hedgren, Amanda, and Daniel Genberg. "Multi criteria decision making approach for strategic evaluation of environmental trade-off solution in logistics : A case study at Northvolt." Thesis, Luleå tekniska universitet, Institutionen för ekonomi, teknik, konst och samhälle, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-85731.

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The purpose of this thesis is to investigate to what extent the environmental agenda should be taken into consideration during the project phase of logistics at Northvolt. The objective is to build an optimization model for route planning with a trade-off solution for three criteria; cost, emission and time. An abductive research approach is used. The empirical data was collected quantitatively in accordance with cross-industry standard process for data mining. The results obtained from the optimization model were based on an emission calculation framework and weights assigned to the three selected criteria by five decision makers. These results are compared to an as-is analysis of current and of historical transportations as well as to expected future transportations. These results provide insights and emphasize the importance of agility in decision making aiming at the reduction of emissions. The analysis shows that increased costs do not have a clear correlation with reduced emissions or transportation time. It also demonstrates that transporting goods on sea would increase the transportation time but decrease the emissions. The conclusions of the study are that costs can be reduced by 8%, emissions by 6% and transportation time by 14%, compared to their current operations. Short-term recommendations address the need of being agile in the route planning and analyse each shipment individually where the weights of the criteria should be alternated depending on the status of the project. This requires increased communication with the installation team on site and negotiation of contractual rates from additional ports in Sweden. Long-term recommendations emphasise the importance of developing and using emission key performance indicators to set targets in combination with a strategy in order to steer daily operations.
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Di, Teodoro Alessandro. "Teoria dei giochi e Multi-criteria decision-making per reti mobili Ad-hoc: un protocollo di routing." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/6594/.

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Nell'elaborato si analizzano aspetti della teoria dei giochi e della multi-criteria decision-making. La riflessione serve a proporre le basi per un nuovo modello di protocollo di routing in ambito Mobile Ad-hoc Networks. Questo prototipo mira a generare una rete che riesca a gestirsi in maniera ottimale grazie ad un'acuta tecnica di clusterizzazione. Allo stesso tempo si propone come obiettivo il risparmio energetico e la partecipazione collaborativa di tutti i componenti.
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Kirlangicoglu, Cem. "A New Census Geography For Turkey Using Geographic Information Systems A Case Study On Cankaya District, Ankara." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606144/index.pdf.

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Today, population census results are not only fundamental for population counting but also for providing various information to many organizations and people who make research and take decisions about human-related issues. However, statistics produced on the basis of administrative divisions in Turkey are inadequate to meet the needs of most In this study, a new census geography is aimed for Turkey using Geographic Information Systems and Multi Criteria Decision Making methodologies. This new census geography is for statistical purposes only, independent from legal boundaries and generated by the concept of small area statistics. New rules and methodologies are created by taking the United States and the United Kingdom systems as models to reach to the main aim, and then they are applied on a case study area, Ç
ankaya District in Ankara. Through this application process, firstly all the collected graphical and nongraphical raw data are geo-referenced and combined in a common geodatabase. Secondly, this geodatabase is used to understand the differentiation of quality of life indicators across the case study area. This pattern is then used to draw the boundaries of small statistical units of the new census geography in terms of the previously defined population sizes. In conclusion, a nationwide standard census geography hierarchy, which ranges between national level at the top and block level at the bottom, is proposed for use in 2010 Population Census and afterwards.
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Books on the topic "Multi-criteria Decision Making (MCDM) techniques"

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Massam, Bryan H. Multi-criteria decision making (MCDM) techniques in planning. Oxford: Pergamon, 1988.

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Massam, B. H. Multi-criteria decision making (MCDM) techniques in planning. Oxford: Pergamon Press, 1988.

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Brugha, Cathal M. Differentiating attributes of decision alternatives from criteria of decision makers in multi criteria decision making (MCDM). Dublin: University College Dublin, Dept of Management Information Systems, 1997.

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Diamond, D. R. Multi-Criteria Decision Making (MCDM) Techniques in Planning. Pergamon Pr, 1988.

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Multiple-Criteria Decision-Making (MCDM) Techniques for Business Processes Information Management. MDPI, 2019. http://dx.doi.org/10.3390/books978-3-03897-643-1.

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Chatterjee, Prasenjit, Suchismita Satapathy, and Debesh Mishra. Multi-Criteria Decision-making Techniques in Waste Management. Taylor & Francis Group, 2021.

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Multi-Criteria Decision-Making Techniques for Improvement Sustainability Engineering Processes. MDPI, 2020. http://dx.doi.org/10.3390/books978-3-03936-779-5.

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Multi-Criteria Decision-Making Techniques for Improvement Sustainability Engineering Processes: Volume 2. MDPI, 2020. http://dx.doi.org/10.3390/books978-3-03936-793-1.

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Chatterjee, Prasenjit, Suchismita Satapathy, and Debesh Mishra. Multi-Criteria Decision-Making Techniques in Waste Management: A Case Study of India. Apple Academic Press, Incorporated, 2021.

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Chatterjee, Prasenjit, Suchismita Satapathy, and Debesh Mishra. Multi-Criteria Decision-Making Techniques in Waste Management: A Case Study of India. Apple Academic Press, Incorporated, 2021.

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Book chapters on the topic "Multi-criteria Decision Making (MCDM) techniques"

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Majumder, Mrinmoy, and Apu K. Saha. "Multi Criteria Decision Making." In Feasibility Model of Solar Energy Plants by ANN and MCDM Techniques, 9–12. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-287-308-8_3.

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Tecle, Aregai, and Lucien Duckstein. "A Procedure for Selecting MCDM Techniques for Forest Resources Management." In Multiple Criteria Decision Making, 19–32. New York, NY: Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4612-2918-6_2.

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Bajal, Eshan, Alakananda Chakraborty, Muskan Jindal, and Shilpi Sharma. "Application of the MCDM Technique for an Astute Decision-Making Process in the Renewable Energy Sector." In Multi-Criteria Decision Modelling, 83–106. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003125150-5-5.

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Gichamo, Tagesse, Hüseyin Gökçekuş, Dilber Uzun Ozsahin, Gebre Gelete, and Berna Uzun. "Ranking of Natural Wastewater Treatment Techniques by Multi-criteria Decision Making (MCDM) Methods." In Application of Multi-Criteria Decision Analysis in Environmental and Civil Engineering, 87–100. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-64765-0_11.

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Adak, Amal Kumar, Nilkamal, and Kaushila Nandan Srivastava. "New Ranking Approach to Solve MCDM Problems with Generalized Intuitionistic Fuzzy Information." In Real Life Applications of Multiple Criteria Decision Making Techniques in Fuzzy Domain, 559–66. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4929-6_26.

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Beldek, Tuğçe, Aziz Kemal Konyalıoğlu, and Hatice Camgöz-Akdağ. "A Fuzzy MCDM Approach for Project Selection Criteria Prioritization in a Big-Four Company: Evidences from Turkey Consultancy Sector." In Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making, 796–803. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23756-1_95.

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Jeong, Jin Su, David González-Gómez, and Félix Yllana-Prieto. "Multi-criteria Decision Analysis and Fuzzy-Decision-Making Trial and Evaluation Laboratory (MCDA and F-DEMATEL) Method for Flipped and Sustainable Mathematics Teaching as a Real-Life Application." In Real Life Applications of Multiple Criteria Decision Making Techniques in Fuzzy Domain, 105–23. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4929-6_5.

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Gass, Saul I., and Carl M. Harris. "Multi-criteria decision making (MCDM)." In Encyclopedia of Operations Research and Management Science, 531. New York, NY: Springer US, 2001. http://dx.doi.org/10.1007/1-4020-0611-x_646.

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Singh, Davinder, Jaimal Singh Khamba, and Tarun Nanda. "Multi-criteria decision-making techniques." In Technology Innovation in Manufacturing, 47–62. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003272977-5.

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Singh, Chandan Deep, and Jaimal Singh Khamba. "Multi-Criteria Decision-Making Techniques." In Manufacturing Competency and Strategic Success in the Automobile Industry, 141–70. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, 2019.: CRC Press, 2019. http://dx.doi.org/10.1201/9780429486302-6.

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Conference papers on the topic "Multi-criteria Decision Making (MCDM) techniques"

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Fleming, Peter J. "Tools and Techniques for Managing Many-Criteria Decision-Making." In 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making. IEEE, 2007. http://dx.doi.org/10.1109/mcdm.2007.369411.

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Kornyshova, E., and C. Salinesi. "MCDM Techniques Selection Approaches: State of the Art." In 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making. IEEE, 2007. http://dx.doi.org/10.1109/mcdm.2007.369412.

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Yeung, S. H., K. F. Man, and W. S. Chan. "ISM Band Antenna Design Based on Fuzzy MCDM Selection Technique." In 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making. IEEE, 2007. http://dx.doi.org/10.1109/mcdm.2007.369437.

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Yoshikawa, Tomohiro, Daisuke Yamashiro, and Takeshi Furuhashi. "A Proposal of Visualization of Multi-Objective Pareto Solutions -Development of Mining Technique for Solutions-." In 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making. IEEE, 2007. http://dx.doi.org/10.1109/mcdm.2007.369433.

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Sabina Sánchez, Helem, Ramón Vilanova, Antonio Visioli, and Orlando Arrieta. "Nash solution as a multi-criteria decision making technique for control problems." In Actas de las XXXVII Jornadas de Automática 7, 8 y 9 de septiembre de 2016, Madrid. Universidade da Coruña, Servizo de Publicacións, 2022. http://dx.doi.org/10.17979/spudc.9788497498081.1243.

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. A control system problem can be viewed as a multi- objective problem due to the fact that there are many requirements to be satisfied. Nowadays, multi-objective optimization deals with this kind of problem by implementing optimization techniques, capable of searching for the Pareto set approximation, hereafter the designer needs to select the best solution that provides a good trade-off among the competitive objectives from the Pareto front approximation. Therefore, in this communication we address the problem of selecting the best trade-o_ between the conflictive objectives, this stage is called the Multi-Criteria Decision Making (MCDM). In this paper we propose to use the Nash solution as a tuning technique to select the design alternative to implement on the control system. This selection is compared with others Proportional-Integral (PI) tuning rules on the literature.
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Balali, Amirhossein, Akilu Yunusa-Kaltungo, and Rodger Edwards. "A Systematic Literature Review of Passive Energy Consumption Optimisation Strategies in Buildings and Their Selection Criteria." In ASME 2022 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/imece2022-93887.

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Abstract Buildings are essential to the development and sustainability of any society, due to the criticality of their residential, commercial and educational roles. However, the building sector has also been classified as highly energy-intensive, due to its ever-rising annual energy consumption trends. Buildings’ energy consumption rate is in fact expected to increase further over the coming years, due to current trends of global population growth. It is therefore imperative to deduce and implement strategies that would improve the sustainability of energy within the built environment. Taking advantage of passive energy consumption optimisation strategies is an apt alternative in this case. However, the procedure of selecting the best passive energy consumption optimisation strategy, including selection of the passive strategy itself, selection criteria and selection method, has been a challenge for buildings’ experts. The use of Multiple Criteria Decision Analysis (MCDA)/Multiple Criteria Decision-Making (MCDM) approaches have proven useful for aiding the selection of alternatives based on multiple criteria in numerous studies during recent years. However, there are several techniques within the MCDA/MCDM class of techniques, which make the selection process rather convoluted. Therefore, the overarching aim of the current study is to generate the most prevalent passive energy consumption optimisation strategies for buildings, the criteria for their selections and the corresponding MCDA/MCDM techniques that aided such selections. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Procedure for Performing Systematic Reviews (PPSR) were used to conduct the current systematic literature review (SLR). The SLR examined research articles that are domiciled within very popular databases such as Compendex, GEOBASE, GeoRef, Inspec, Web of Science (WoS) and Scopus, based on meticulously constructed keywords. It was observed that limited passive strategies, selection criteria and MCDM/MCDA techniques were considered in the investigated articles, making it a serious gap in the body of knowledge, which needs accurate consideration for future studies. For instance, it was observed that most studies focussed on particular passive strategies such as optimisation of insulation thickness and location, natural ventilation envelope, etc., while other strategies such as thermal bridge reduction, enhancing vapour tightness and natural daylighting are underrepresented. The results of the SLR are hereby provided and discussed in the current study.
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Fernandez, Charles, Arun Kr Dev, Rose Norman, Wai Lok Woo, and Shashi Bhushan Kumar. "Dynamic Positioning System: Systematic Weight Assignment for DP Sub-Systems Using Multi-Criteria Evaluation Technique Analytic Hierarchy Process and Validation Using DP-RI Tool With Deep Learning Algorithm." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95485.

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Abstract The Dynamic Positioning (DP) System of a vessel involves complex interactions between a large number of sub-systems. Each sub-system plays a unique role in the continuous overall DP function for safe and reliable operation of the vessel. Rating the significance or assigning weightings to the DP sub-systems in different operating conditions is a complex task that requires input from many stakeholders. The weighting assignment is a critical step in determining the reliability of the DP system during complex marine and offshore operations. Thus, an accurate weighting assignment is crucial as it, in turn, influences the decision-making of the operator concerning the DP system functionality execution. Often DP operators prefer to rely on intuition in assigning the weightings. However, it introduces an inherent uncertainty and level of inconsistency in the decision making. The systematic assignment of weightings requires a clear definition of criteria and objectives and data collection with the DP system operating continuously in different environmental conditions. The sub-systems of the overall DP system are characterized by multi-attributes resulting in a high number of comparisons thereby making weighting distribution complicated. If the weighting distribution was performed by simplifying the attributes, making the decision by excluding part of them or compromising the cognitive efforts, then this could lead to inaccurate decision making. Multi-Criteria Decision Making (MCDM) methods have evolved over several decades and have been used in various applications within the Maritime and Oil and Gas industries. DP, being a complex system, naturally lends itself to the implementation of MCDM techniques to assign weight distribution among its sub-systems. In this paper, the Analytic Hierarchy Process (AHP) methodology is used for weight assignment among the DP sub-systems. An AHP model is effective in obtaining the domain knowledge from numerous experts and representing knowledge-guided indexing. The approach involved examination of several criteria in terms of both quantitative and qualitative variables. A state-of-the-art advisory decision-making tool, Dynamic Positioning Reliability Index (DP-RI), is used to validate the results from AHP. The weighting assignments from AHP are close to the reality and verified using the tool through real-life scenarios.
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Ajripour, Iman. "Applying MCDM Technique in analyzing the effect of promotion items based on online shopping factors." In The European Union’s Contention in the Reshaping Global Economy. Szeged: Szegedi Tudományegyetem Gazdaságtudományi Kar, 2020. http://dx.doi.org/10.14232/eucrge.2020.proc.1.

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Developing technology causes companies in a market to compete with each other in challenging ways. In addition to a holistic marketing concept which focuses on the needs of target markets and delivering superior value, marketing should be adapted with new technology to fulfill consumer needs. Although many strategies have been introduced for marketing, digital marketing or marketing 4.0 is a new generation of marketing that engages with the audience through digital tools. These days, online shopping is only too popular among consumers. Many factors which affect customer decision during online shopping have been explored. In this paper, the effect of promotion items in online shopping will be explained. The main aim of this paper is to apply a multi-criteria decision-making technique in prioritizing eleven promotion items by considering five online customer shopping criteria. The novelty of this paper is to apply PROMETHEE II (Preference Ranking Organization METHod for Enrichment of Evaluations) in analyzing the effect of promotion items based on online shopping criteria. PROMETHEE II completely prioritizes discrete alternatives. A case study is conducted in a home appliance company in Iran.
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Poon Chong, Peter, and Terrence Lalla. "APPLYING FUZZY QFD MCDM TO EVALUATE MUSICAL INSTRUMENTS." In International Conference on Emerging Trends in Engineering & Technology (IConETech-2020). Faculty of Engineering, The University of the West Indies, St. Augustine, 2020. http://dx.doi.org/10.47412/bgmj4037.

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This paper exhibits a method to improve the quality of musical instruments with the application of two Multi-Criteria Decision Making models, Technique of Order Preference by Similarity to Ideal Solution (TOPSIS) and Analytic Hierarchy Process (AHP) in a Quality Function Deployment (QFD) Environment. A fuzzy analysis approach was also included to accommodate qualitative data in music. The QFD was constructed with literature based on optimizing the manufacture of musical instruments. At this phase of the research, the paper focused on the physical parameters and perceived qualities of musical instruments. The proposed modified QFD was developed to identify the product features chosen by the market and aid the manufacture of musical instruments. A standard QFD recognized and scored factors to develop and manufacture musical instruments. It accommodated some core engineering variables for the musical instruments but overlooked some feature stakeholder needs. For example, the musician may not have 100% gratification while playing the instrument as the manufacturer fails to capture acoustic features to psychologically satisfy the musician’s audience. Using fuzzy logic, QFD and MCDM increased the model performance by expanding the data set. It offered the manufacturer of musical instruments a mode to capture and analyse behavioural linguistic data covering more customer requirements. Hence, the approach increased the range to correlate the physical features and psychological behaviours of musical instruments. It allowed non-technical persons to provide an improved form of reliable information. This modified QFD can also be applied to develop other products involving linguistic data.
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Göktolga, Ziya Gökalp, Engin Karakış, and Hakan Türkay. "Comparison of the Economic Performance of Turkish Republics in Central Asia with TOPSIS Method." In International Conference on Eurasian Economies. Eurasian Economists Association, 2015. http://dx.doi.org/10.36880/c06.01270.

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The aim of this study is to compare the economic performance of Turkish Republics in Central Asia with Multi Criteria Decision Making (MCDM) methods. Turkish Republics have been experiencing a transition from a centrally planned economy towards a market economy since their independence. In this study important macroeconomic indicators are used to determine economic performance. Economic performance evaluation of the country is an important issue for economic management, investors, creditors and stock investors. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method outranks the countries according to the proximity of the positive ideal solution and distance of the negative ideal solution. Economic Performance of Turkish Republics in Central Asia (Azerbaijan, Turkmenistan, Kazakhstan, Kyrgyzstan, and Uzbekistan) are compared with TOPSIS method. İnvestigated with TOPSIS method countries best and worst economic performance years are detected during mentioned period and results are analyzed.
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Reports on the topic "Multi-criteria Decision Making (MCDM) techniques"

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Karam, Sofia, Morteza Nagahi, Vidanelage Dayarathna, Junfeng Ma, Raed Jaradat, and Michael Hamilton. Integrating systems thinking skills with multi-criteria decision-making technology to recruit employee candidates. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/41026.

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The emergence of modern complex systems is often exacerbated by a proliferation of information and complication of technologies. Because current complex systems challenges can limit an organization's ability to efficiently handle socio-technical systems, it is essential to provide methods and techniques that count on individuals' systems skills. When selecting future employees, companies must constantly refresh their recruitment methods in order to find capable candidates with the required level of systemic skills who are better fit for their organization's requirements and objectives. The purpose of this study is to use systems thinking skills as a supplemental selection tool when recruiting prospective employees. To the best of our knowledge, there is no prior research that studied the use of systems thinking skills for recruiting purposes. The proposed framework offers an established tool to HRM professionals for assessing and screening of prospective employees of an organization based on their level of systems thinking skills while controlling uncertainties of complex decision-making environment with the fuzzy linguistic approach. This framework works as an expert system to find the most appropriate candidate for the organization to enhance the human capital for the organization.
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