Dissertations / Theses on the topic 'Fuzzy multi-Criteria analysis'

The Subsea blowout preventer (BOP) which is latched to a subsea wellhead is one of several barriers in the well to prevent kicks and blowouts and it is the most important and critical equipment, as it becomes the last line of protection against blowout. The BOP system used in Subsea drilling operations is considered a Safety – Critical System, with a high severity consequence following its failure. Following past offshore blowout incidents such as the most recent Macondo in the Gulf of Mexico, there have been investigations, research, and improvements sought for improved understanding of the BOP system and its operation. This informs the need for a systematic re-evaluation of the Subsea BOP system to understand its associated risk and reliability and identify critical areas/aspects/components. Different risk analysis techniques were surveyed and the Failure modes effect and criticality analysis (FMECA) selected to be used to drive the study in this thesis. This is due to it being a simple proven cost effective process that can add value to the understanding of the behaviours and properties of a system, component, software, function or other. The output of the FMECA can be used to inform or support other key engineering tasks such as redesigning, enhanced qualification and testing activity or maintenance for greater inherent reliability and reduced risk potential. This thesis underscores the application of the FMECA technique to critique associated risk of the Subsea BOP system. System Functional diagrams was developed with boundaries defined, a FMECA were carried out and an initial select list of critical component failure modes identified. The limitations surrounding the confidence of the FMECA failure modes ranking outcome based on Risk priority number (RPN) is presented and potential variations in risk interpretation are discussed. The main contribution in this thesis is an innovative framework utilising Multicriteria decision making (MCDA) analysis techniques with consideration of fuzzy interval data is applied to the Subsea BOP system critical failure modes from the FMECA analysis. It utilised nine criticality assessment criteria deduced from expert consultation to obtain a more reliable ranking of failure modes. The MCDA techniques applied includes the technique for order of Preference for similarity to the Ideal Solution (TOPSIS), Fuzzy TOPSIS, TOPSIS with interval data, and Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE). The outcome of the Multi-criteria analysis of the BOP system clearly shows failures of the Wellhead connector, LMRP hydraulic connector and Control system related failure as the Top 3 most critical failure with respect to a well control. The critical failure mode and components outcome from the analysis in this thesis is validated using failure data from industry database and a sensitivity analysis carried out. The importance of maintenance, testing and redundancy to the BOP system criticality was established by the sensitivity analysis. The potential for MCDA to be used for more specific analysis of criteria for a technology was demonstrated. Improper maintenance, inspection, testing (functional and pressure) are critical to the BOP system performance and sustenance of a high reliability level. Material selection and performance of components (seals, flanges, packers, bolts, mechanical body housings) relative to use environment and operational conditions is fundamental to avoiding failure mechanisms occurrence. Also worthy of notice is the contribution of personnel and organisations (by way of procedures to robustness and verification structure to ensure standard expected practices/rules are followed) to failures as seen in the root cause discussion. OEMs, operators and drilling contractors to periodically review operation scenarios relative to BOP system product design through the use of a Failure reporting analysis and corrective action system. This can improve design of monitoring systems, informs requirement for re-qualification of technology and/or next generation designs. Operations personnel are to correctly log in failures in these systems, and responsible Authority to ensure root cause analysis is done to uncover underlying issue initiating and driving failures.

This research develops a Fuzzy Multi-Attribute Analysis (FMAA) model to select the most appropriate contractors for Engineering-Procurement-Construction (EPC) projects. It will enable EPC project owners to eliminate the over-reliance on subjective contractor selection and risks associated with incomplete information, imprecise data and vagueness in human decision making. With the combination of fuzzy set theory and multi-attribute analysis, this model addresses the fuzzy nature in human decision making and helps EPC clients achieve the best value of the contract.

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.

In an ever-changing world as ours, the population increases rapidly. There will be great challenges for urban planning when it comes to finding effective, optimized and sustainable solutions. The city planners must find the most optimal way of land usage and one way of reaching this can be obtained through a land-suitability analysis. Land-suitability analysis can be described as a combination of both Geographic information system (GIS) and Multi-criteria analysis (MCA) and is used to obtain the most optimal position for a specific land usage, e.g. residential areas. GIS and MCA can both be used separately but can also be used as described in a combination. The aim of this study is to compare two different municipalities, Nordanstig and Sundsvall, and how the weighting of social functions in planning housing projects differs in them. Another purpose is to compare two different MCA weighting methods and how they affect the final results. The methods used were Analytical Hierarchical Process (AHP) and Fuzzy AHP (FAHP). Using the output of the poll and the interviews from the representatives of the two municipalities weights were computed. The purpose of the study is to find suitable locations where residential areas can be built. The result of the study shows that the officials ranked the weights of the social functions in a new residential area differently. The respondent from Sundsvall ranks public transportation as the most important factor, while the respondent from Nordanstig ranks larger road/railway the highest. The final results end up in the same urban areas in both AHP and Fuzzy AHP methods. The main differences between them are the sizes of the areas and their exact extents. The biggest area was achieved through Sundsvall’s FAHP weighting and was located in the urban area of Gnarp. The area was about 118.5 hectare in size. To check whether the results can be considered appropriate a sensitivity analysis has been performed, using inverted weights taken from the poll and the interviews.
I en värld där befolkningen ökar kraftigt och är i ständig förändring, där ställs samhället och dess beslutsfattare inför stora utmaningar. En av dessa utmaningar är att planera samhällen på ett effektivt och optimerat sätt, som även innefattar hållbara lösningar. Med en strävan att på bästa sätt använda marken i staden, samhället och landet så kan en lämplighetsanalys användas. En lämplighetsanalys är en kombination av att använda Geografisk informationssystem (GIS) och multikriterieanalys (MKA) för att få fram den mest lämpliga platsen som för exempel ett bostadsområde. Både GIS och MKA är var för sig viktiga delar i samhället som även kan användas i kombination. Studiens syfte är att jämföra två kommuner, Nordanstig och Sundsvalls kommun, och deras olika viktning av samhällsfunktioner vid bostadsplanering. Det andra syftet är att jämföra hur två olika MKA metoder påverkar de slutliga resultaten. De två olika metoderna är Analytisk hierarkisk process (AHP) och Fuzzy AHP. Med hjälp av enkät och intervjuer av representanterna från kommunerna så tas vikter fram. De tillfrågade var tjänstemän från de två kommunerna, en från vardera kommunen. Målet med studien är att få fram områden där bostadsområden kan byggas, med hjälp av en multikriterieanalys. En bostadsplanering som tar in hållbarhets aspekter tidigt strävar mot att bidra till ett miljövänligare samhälle, aspekter som busshållplatser och park och fritid. Resultatet visar att de olika tjänstemännen rangordnar kriterierna olika på vad som är viktigast när det kommer till samhällsfunktioner i ett nytt bostadsområde. Representanten från Sundsvall rangordnar Kollektivtrafiken högst och representanten från Nordanstig rangordnar Större väg/järnväg högst. Slutresultatet visar att placering av bostadsområdet hamnar vid AHP metoden ungefär vid samma orter som vid Fuzzy AHP metoden. Det som skiljer är storleken på de olika områden och deras mer exakta utbredning. Det största området blir enligt Sundsvall viktning till FAHP och beläget i tätorten Gnarp, ytan blir då ca 118,5 ha stor. För att kontrollera om resultatet kan anses vara lämpligt har en känslighetsanalys gjorts, genom inverterade vikter tagna från enkäten och intervjuerna.

In questo lavoro si affronta il problema di applicare le politiche di manutenzione preventive su un impianto in avviamento, non conoscendo o conoscendo poco i dati storici, necessari all'ottimizzazione o all'applicazione di una strategia manutentiva. Tramite lo studio e l'analisi della letteratura si cerca di determinare quali tecniche o procedure vengono implementate per superare la mancanza di dati. Dopo l'analisi degli autori e l'introduzione delle tecniche utilizzate si propone una procedura in grado di coniugare costi, qualità e sicurezza.

This project developed a new method to address sustainability aspects relevant to the location of biomass energy plants. The method is based on an integrated geographical information system model to identify optimal sites for biomass energy supply, incorporating spatial biomass availability, and economic, environmental and biomass specific uncertainties in the biomass supply chain. The analysis was carried out in Queensland, Australia as a case study, demonstrating the potential of multiple biomass sources for biomass energy supply.

En sciences économiques, l'une des questions centrales concerne l'allocation des ressources rares et plus particulièrement leur répartition. La décision apparait ainsi au cœur des thématiques économiques, que ce soit en micro-économie ou en macro-économie. Dans un premier temps, nous revenons sur le fait que l’information, élément central de la prise de décision, est imparfaite. En utilisant la théorie des ensembles flous, qui a pour objet de capturer l’imprécision, nous construisons un nombre flou nommé nombre flou C-Shape qui permet de capter la sensibilité du preneur de décision. Nous étudions ensuite la théorie de la décision au travers de deux axes de recherche à savoir (1) la recherche opérationnelle couplée à la théorie des jeux et (2) l’aide à la décision. En premier lieu, Nous faisons une analogie entre la fonction distance et la fonction d’appartenance. Grâce à l’hypothèse de B-convexité et à la fonction C-Shape nous construisons des classes de jeux pour lesquels les joueurs peuvent être optimistes, pessimistes ou neutres, et pour lesquels l’existence d’équilibre de Nash est avérée. Enfin, concernant l’aide à la décision, nous utilisons la fonction C-Shape pour caractériser un nouveau type de critère nommé pseudo critère C-Shape qui permet de considérer les alternatives comme substituables. Ceci permet de prendre en compte, par exemple le contexte institutionnel dans lequel la prise de décision est prise
Determining the allocation and the distribution of scarce resources is fundamental in economics. Thus, decision theory is the cornerstone of economic theory. In this thesis, we first provide a state of the art insisting on the fact that information, that is a central element of decision-making, is imperfect. Secondly, using fuzzy set theory, which aims to capture imprecision, we construct a fuzzy number, so-called C-Shape that captures the sensitivity of the decision-maker. Thirdly, we study decision theory through two key concepts of operation research: (1) game theory and (2) multi-criteria decision making. We provide an analogy between the gauge functions of convex sets and the membership functions arising in fuzzy set theory. Coupling a suitable notion of -convexity with the C-Shape function, we introduce a class of games for which the players can be optimistic, pessimistic or neutral. In addition the existence of Nash equilibrium is proved for such a class of games. Finally, concerning multi-criteria decision analysis, we use the C-Shape functions to characterize a new type of criteria called C-Shape pseudo-criterion, which makes possible to consider the alternatives as substitutable. This should be of interest to take into account, for example, the institutional context in which decision-making is taken

Human hair profiling is an integral part of a forensic investigation but it is one of the most technically difficult subjects in forensic science. This thesis describes the research and development of a novel approach for the rapid identification of unknown human and other related keratin fibres found at a crime scene. The work presented here is developed systematically and considers sample collection, sample preparation, analysis and interpretation of spectral data for the profiling of hair fibres encountered in criminal cases. Spectral comparison of fibres was facilitated with the use of chemometrics methods such as PCA, SIMCA and Fuzzy Clustering, and the less common approach of multi-criteria decision making methodology (MCDM). The aim of the thesis was to investigate the potential of some vibrational spectroscopy techniques for matching and discrimination of single keratin hair fibres in the context of forensic evidence. The first objective (chapter 3) of the thesis was to evaluate the use of Raman and FT-IR micro-spectroscopy techniques for the forensic sampling of hair fibres and to propose the preferred technique for future forensic hair comparisons. The selection of the preferred technique was based on criteria such as spectral quality, ease of use, rapid analysis and universal application to different hair samples. FT-IR micro-spectroscopy was found to be the most appropriate technique for hair analysis because it enabled the rapid collection of spectra from a wide variety of hair fibres. Raman micro-spectroscopy, on the other hand, was hindered with fluorescence problems and did not allow the collection of spectra from pigmented fibres. This objective has therefore shown that FT-IR micro-spectroscopy is the preferable spectroscopic technique for forensic analysis of hair fibres, whilst Raman spectroscopy is the least preferred. The second objective (chapter 3) was to investigate, through a series of experiments, the effect of chemical treatment on the micro-environment of human hair fibres. The effect of bleaching agents on the hair fibres was studied with some detail at different treatment times and the results indicate a significant change in the chemical environment of the secondary structure of the hair fibre along with changes in the C-C backbone structure. One of the most important outcomes of this research was the behaviour of the fÑ-helix during chemical treatment. The hydrogen bonding in the fÑ-helix provides for the stable structure of the fibre and therefore any disruption to the fÑ-helix will inevitably damage the molecular structure of the fibre. The results highlighted the behaviour of the fÑ-helix, which undergoes a significant decrease in content during oxidation, and is partly converted to a random-coil structure, whilst the fÒ-sheet component of the secondary structure remains unaffected. The reported investigations show that the combination of FT-IR and Raman micro-spectroscopy can provide an insight and understanding into the complex chemical properties and reactions within a treated hair fibre. Importantly, this work demonstrates that with the aid of chemometrics, it is possible to investigate simultaneously FT-IR and Raman micro-spectroscopic information from oxidised hair fibres collected from one subject and treated at different times. The discrimination and matching of hair fibres on the basis of treatment has potential forensic applications. The third objective (chapter 4) attempted to expand the forensic application of FT-IR micro-spectroscopy to other keratin fibres. Animal fibres are commonly encountered in crime scenes and it thus becomes important to establish the origin of those fibres. The aim of this work was to establish the forensic applications of FT-IR micro-spectroscopy to animal fibres and to investigate any fundamental molecular differences between these fibres. The results established a discrimination between fibres consisting predominantly of fÑ-helix and those containing mainly a fÒ-sheet structure. More importantly, it was demonstrated through curve-fitting and chemometrics, that each keratin fibre contains a characteristic secondary structure arrangement. The work presented here is the first detailed FT-IR micro-spectroscopic study, utilising chemometrics as well as MCDM methods, for a wide range of keratin fibres, which are commonly, found as forensic evidence. Furthermore, it was demonstrated with the aid of the rank ordering MCDM methods PROMETHEE and GAIA, that it is possible to rank and discriminate keratin fibres according to their molecular characteristics obtained from direct measurements together with information sourced from the literature. The final objective (chapter 5) of the thesis was to propose an alternative method for the discrimination and matching of single scalp human hair fibres through the use of FT-IR micro-spectroscopy and chemometrics. The work successfully demonstrated, through a number of case scenarios, the application of the technique for the identification of variables such as gender and race for an unknown single hair fibre. In addition, it was also illustrated that known hair fibres (from the suspect or victim) can be readily matched to the unknown hair fibres found at the crime scene. This is the first time that a substantial, systematic FT-IR study of forensic hair identification has been presented. The research has shown that it is possible to model and correlate individual¡¦s characteristics with hair properties at molecular level with the use of chemometrics methods. A number of different, important forensic variables of immediate use to police in a crime scene investigation such as gender, race, treatment, black and white hair fibres were investigated. Blind samples were successfully applied both to validate available experimental data and extend the current database of experimental determinations. Protocols were posed for the application of this methodology in the future. The proposed FT-IR methodology presented in this thesis has provided an alternative approach to the characterisation of single scalp human hair fibres. The technique enables the rapid collection of spectra, followed by the objective analytical capabilities of chemometrics to successfully discriminate animal fibres, human hair fibres from different sources, treated from untreated hair fibres, as well as black and white hair fibres, on the basis of their molecular structure. The results can be readily produced and explained in the courts of law. Although the proposed relatively fast FT-IR technique is not aimed at displacing the two slower existing methods of hair analysis, namely comparative optical microscopy and DNA analysis, it has given a new dimension to the characterisation of hair fibres at a molecular level, providing a powerful tool for forensic investigations.

Human hair profiling is an integral part of a forensic investigation but it is one of the most technically difficult subjects in forensic science. This thesis describes the research and development of a novel approach for the rapid identification of unknown human and other related keratin fibres found at a crime scene. The work presented here is developed systematically and considers sample collection, sample preparation, analysis and interpretation of spectral data for the profiling of hair fibres encountered in criminal cases. Spectral comparison of fibres was facilitated with the use of chemometrics methods such as PCA, SIMCA and Fuzzy Clustering, and the less common approach of multi-criteria decision making methodology (MCDM). The aim of the thesis was to investigate the potential of some vibrational spectroscopy techniques for matching and discrimination of single keratin hair fibres in the context of forensic evidence. The first objective (chapter 3) of the thesis was to evaluate the use of Raman and FT-IR micro-spectroscopy techniques for the forensic sampling of hair fibres and to propose the preferred technique for future forensic hair comparisons. The selection of the preferred technique was based on criteria such as spectral quality, ease of use, rapid analysis and universal application to different hair samples. FT-IR micro-spectroscopy was found to be the most appropriate technique for hair analysis because it enabled the rapid collection of spectra from a wide variety of hair fibres. Raman micro-spectroscopy, on the other hand, was hindered with fluorescence problems and did not allow the collection of spectra from pigmented fibres. This objective has therefore shown that FT-IR micro-spectroscopy is the preferable spectroscopic technique for forensic analysis of hair fibres, whilst Raman spectroscopy is the least preferred. The second objective (chapter 3) was to investigate, through a series of experiments, the effect of chemical treatment on the micro-environment of human hair fibres. The effect of bleaching agents on the hair fibres was studied with some detail at different treatment times and the results indicate a significant change in the chemical environment of the secondary structure of the hair fibre along with changes in the C-C backbone structure. One of the most important outcomes of this research was the behaviour of the fÑ-helix during chemical treatment. The hydrogen bonding in the fÑ-helix provides for the stable structure of the fibre and therefore any disruption to the fÑ-helix will inevitably damage the molecular structure of the fibre. The results highlighted the behaviour of the fÑ-helix, which undergoes a significant decrease in content during oxidation, and is partly converted to a random-coil structure, whilst the fÒ-sheet component of the secondary structure remains unaffected. The reported investigations show that the combination of FT-IR and Raman micro-spectroscopy can provide an insight and understanding into the complex chemical properties and reactions within a treated hair fibre. Importantly, this work demonstrates that with the aid of chemometrics, it is possible to investigate simultaneously FT-IR and Raman micro-spectroscopic information from oxidised hair fibres collected from one subject and treated at different times. The discrimination and matching of hair fibres on the basis of treatment has potential forensic applications. The third objective (chapter 4) attempted to expand the forensic application of FT-IR micro-spectroscopy to other keratin fibres. Animal fibres are commonly encountered in crime scenes and it thus becomes important to establish the origin of those fibres. The aim of this work was to establish the forensic applications of FT-IR micro-spectroscopy to animal fibres and to investigate any fundamental molecular differences between these fibres. The results established a discrimination between fibres consisting predominantly of fÑ-helix and those containing mainly a fÒ-sheet structure. More importantly, it was demonstrated through curve-fitting and chemometrics, that each keratin fibre contains a characteristic secondary structure arrangement. The work presented here is the first detailed FT-IR micro-spectroscopic study, utilising chemometrics as well as MCDM methods, for a wide range of keratin fibres, which are commonly, found as forensic evidence. Furthermore, it was demonstrated with the aid of the rank ordering MCDM methods PROMETHEE and GAIA, that it is possible to rank and discriminate keratin fibres according to their molecular characteristics obtained from direct measurements together with information sourced from the literature. The final objective (chapter 5) of the thesis was to propose an alternative method for the discrimination and matching of single scalp human hair fibres through the use of FT-IR micro-spectroscopy and chemometrics. The work successfully demonstrated, through a number of case scenarios, the application of the technique for the identification of variables such as gender and race for an unknown single hair fibre. In addition, it was also illustrated that known hair fibres (from the suspect or victim) can be readily matched to the unknown hair fibres found at the crime scene. This is the first time that a substantial, systematic FT-IR study of forensic hair identification has been presented. The research has shown that it is possible to model and correlate individual¡¦s characteristics with hair properties at molecular level with the use of chemometrics methods. A number of different, important forensic variables of immediate use to police in a crime scene investigation such as gender, race, treatment, black and white hair fibres were investigated. Blind samples were successfully applied both to validate available experimental data and extend the current database of experimental determinations. Protocols were posed for the application of this methodology in the future. The proposed FT-IR methodology presented in this thesis has provided an alternative approach to the characterisation of single scalp human hair fibres. The technique enables the rapid collection of spectra, followed by the objective analytical capabilities of chemometrics to successfully discriminate animal fibres, human hair fibres from different sources, treated from untreated hair fibres, as well as black and white hair fibres, on the basis of their molecular structure. The results can be readily produced and explained in the courts of law. Although the proposed relatively fast FT-IR technique is not aimed at displacing the two slower existing methods of hair analysis, namely comparative optical microscopy and DNA analysis, it has given a new dimension to the characterisation of hair fibres at a molecular level, providing a powerful tool for forensic investigations.

The availability of water can be considered as one of the key ingredients to the human life, yet this resource remains scarcely available to those living in the rural parts of Africa. When water does present itself, it is often impure and requires extensive treatment. Water treatment systems, particularly those capable of treating water in rural areas, are currently areas of research and entrepreneurship focus, making a number of potential solutions available, and other still coming in. Unfortunately, these systems are not always capable of performing in particular socio-cultural and economic contexts, or are often deployed in the wrong rural areas. Therefore these systems do not perform at their optimal level of design. Rural areas in Africa have different socio-cultural and economic context from each other, and this needs to be taken into account if one is going to select the right water treatment system for a particular area. Using industrial engineering tools, two water treatment system selection models; an Additive Analytic Hierarchy Process model and a Fuzzy Logic based model, are presented and then integrated. These models take into account the context of selected rural area by pitting available water purification systems against selected criteria to determine if it is the right fit for the rural area considered. Both models are then pitted against each other to determine which is more adept at selecting the appropriate water purification system. Three water treatment alternatives were considered after an analysis was conducted on the available solutions on the market. The water treatment systems under consideration were the Biosand Filter with Zeolites (BSFZ), the Silver Impregnated Porous Pot, and A Borehole system. Makwane, a rural village in Limpopo, South Africa was used as a case study to demonstrate the application of the selection models. The BSFZ was selected as the ideal water treatment system to be implemented in Makwane
Dissertation (MEng)--University of Pretoria, 2016.
Industrial and Systems Engineering
MEng
Unrestricted

Face à la forte concurrence internationale, de nombreuses entreprises manufacturières orientent leurs investissements vers les marchés africains pour accroître leur part de marché et rester compétitives sur le marché mondial. Ces marchés sont effet en plein essor mais demandent des produits de grande diversité. En dépit de cette attractivité, les flux commerciaux en Afrique demeurent faibles en raison de la faible qualité des infrastructures et de l’absence d’écosystèmes logistiques régionaux connectant les pays africains de manière fiable et efficace.C’est pourquoi cette thèse de doctorat s’intéresse à la modélisation et à la résolution du problème de conception de réseaux de distribution hybrides en Afrique, intégrant des plateformes de distribution et de personnalisation finale des produits. Ces réseaux incluent, en amont, des hubs régionaux servant de porte d’entrée vers les marchés d’une région continentale. Le report de la personnalisation finale en aval du réseau logistique permet de réduire les délais de livraison aux marchés et le coût de distribution tout en maintenant une économie d’échelle. La méthodologie que nous proposons repose sur deux grands axes de recherche :▪ Le premier axe vise à définir la localisation des hubs logistiques régionaux, sur la base d’une analyse multicritères floue, version améliorée de TOPSIS floue et d'AHP ;▪ Le deuxième axe aborde conception de réseaux de distribution hybrides servant des marchés fortement diversifiés (exemple : marchés des engrais). Nous avons proposé deux nouveaux modèles d'optimisation multi-objectifs minimisant le coût total d’exploitation et d’investissement, maximisant la proximité des produits aux marchés et minimisant les dommages sur les produits finis durant leur distribution. Le premier modèle est déterministe tandis que le deuxième propose une conception flexible alignée sur la dynamique et l’incertitude de l’évolution des marchés africains
In the context of intense international competition, many manufacturing firms are directing their investments toward African markets to increase their market share and maintain their competitiveness in the global market. These markets are rapidly growing but require customized products. Despite their attractivity, trade flows in Africa remain low due to the poor quality of infrastructure and the lack of regional logistic ecosystems, connecting African countries through reliable and efficient services.This doctoral thesis therefore focuses on modelling and solving the problem of designing hybrid distribution networks in Africa, integrating distribution and final customization platforms. These networks incorporate, upstream, regional hubs that serve as gateways to regional markets. The postponement of final customization downstream of the logistics network reduces the delivery times and downstream distribution costs while maintaining upstream economies of scale.The methodology we suggest is based on two main areas of research:▪ The first axis aims to define the location of regional logistics hubs, based on a fuzzy multi-criteria analysis approach, which is an improved version of TOPSIS fuzzy and AHP;▪ The second axis focuses on the design of hybrid distribution networks serving highly diversified markets in Africa (for example: fertilizer markets). To this aim, we propose two new multi-objective optimization models minimizing total operating and investment costs, maximizing product proximity to markets and minimizing damage to finished products during their distribution. The first model is deterministic while the second one proposes a flexible design in response to the dynamics and uncertainty of the evolution of African markets

Network screening and countermeasure selection are two crucial steps in the highway improvement process. In network screening, potential improvement locations are ranked and prioritized based on a specific method with a set of criteria. The most common practice by transportation agencies has been to use a simple scoring method, which, in general, weighs and scores each criterion and then ranks the locations based on their relative overall scoring. The method does not deal well with criteria that are qualitative in nature, nor does it account for the impacts of correlation among the criteria. The introduction of Analytic Hierarchy Process (AHP) provides agencies with a method to include both quantitative and qualitative criteria. However, it does not address the issue on correlation. This dissertation explores the use of both Analytic Network Process (ANP) and Fuzzy Analytic Network Process (FANP) for their potential capabilities to address both issues. Using urban four-lane divided highways in Florida for bicycle safety improvements, both ANP and FANP were shown to provide more reasonable rankings than AHP, with FANP providing the best results among the methods. After the locations are ranked and prioritized for improvements, the next step is to evaluate the potential countermeasures for improvements at the selected top-ranked locations. In this step, the standard practice has been to use Crash Modification Factors (CMFs) to quantify the potential impacts from implementing specific countermeasures. In this research, CMFs for bicycle crashes on urban facilities in Florida were developed using the Generalized Linear Model approach with a Zero-Inflated Negative Binomial (ZINB) distribution. The CMFs were tested for their spatial and temporal transferability and the results show only limited transferability both spatially and temporally. The CMFs show that, in general, wider lanes, lower speed limits, and presence of vegetation in the median reduce bicycle crashes, while presence of sidewalk and sidewalk barrier increase bicycle crashes. The research further considered bicycle exposure using the bicycle activity data from the Strava smartphone application. It was found that increased bicycle activity reduces bicycle crash probabilities on segments but increases bicycle crash probabilities at signalized intersections. Also, presence of bus stops and use of permissive signal phasing at intersections were found to increase bicycle crash probabilities.

碩士
國立成功大學
工業與資訊管理學系碩博士班
100
Decision makers select alternatives by using their own subjective opinions . During the evaluation process, vague terms such as “excellent” or “very good” may be used, and in such cases intuitionistic fuzzy sets can be used to aid decision making, as these contain membership and non-membership functions, and can thus provide more information than ordinary fuzzy sets. However, due to the computational complexity and the many factors being considered, it is for decision makers to solve multi-criteria decision-making problems under intuitionistic fuzzy environments. Therefore, this study constructed a multi-criteria decision-making model based on intuitionistic fuzzy sets. The modified TOPSIS method is used to solve multiple attribute group decision making problems under intuitionistic fuzzy environments, and in order to rank various alternatives, this approach utilizes incremental analysis to help select the best sequence in a more objective fashion.

碩士
國立勤益科技大學
流通管理系
97
Selection of new employees is an important study in human resources management, and selecting the employees correctly is the primary factor that influences the operation of enterprise. Different selection criteria would result different evaluations, the evaluation results of some of these criteria can be quantified explicitly, while some of them can be described qualitatively. Therefore, how to include several quantitative and qualitative criteria that the enterprise concerns about into selection model has always been the enterprise’s objective. After changing the study results of interview and personality trait that are used practically into fuzzy data, together with the quantitative scores from the test of professional knowledge, this study applies the effectiveness evaluation model of data envelopment analysis to produce the ranking of job applicants, and this ranking is used as the basis of employing new employees. The fuzzy multi-criteria selection model that this study discusses is contributive to the enterprises so that they can make objective evaluation when the situation is uncertain.

博士
國立交通大學
科技管理研究所
93
Since the World Commission on Environment and Development (WCED) published the so-called Brundtland Report “Our Common Future” in 1987 and the United Nations Environmental Planning Board (UNEP) presented “Agenda 21” in 1992, sustainable development has become an important part of international and national approaches to integrating economic, environmental, social and ethical considerations so that a good quality of life can be enjoyed by current and future generations for as long as possible. In response to the shift in environmental policy and law towards products, most of enterprises have focus on developing sustainable products. For some time, there are many concepts, approaches and tools have been proposed to help industries to meet this aim such as eco-design and sustainable product development. Past empirical researches indicated that these approaches and tools have successfully encouraged the sustainable products and services development for industry. In this study, we firstly survey the stream of sustainable development and recognize the planning process for sustainable products and services development. We also introduce the considered aspects with evaluated criteria in this planning process. In addition, for the reasons of incommensurability and conflicting within these aspects and criteria for sustainable development, the problems will become more complex. Multiple Criteria Decision Analysis (MCDA) can provide appropriately and objectively analysis results for dealing with these kinds of problem. In this empirical study, we firstly employ fuzzy AHP to establish hierarchy system for evaluating the sustainable development strategies of green engineering for fishing industry in Taiwan. Secondly, fuzzy multi-criteria decision analysis method was utilized to derive the final synthetic values of the proposed strategies and determine the preferred order according to these values. In order to conform to the situation of non-independence among evaluated criteria in real problem, we relax the required independence assumption of traditional Analytic Hierarchy Process (AHP) for evaluation. This paper applies λ fuzzy measure and non-additive fuzzy integral technique to derive the synthetic values of proposed strategies. Furthermore, considering the limitation on resources and seldom mutually exclusive among these proposed strategies, we introduce fuzzy classification to find the optimal strategy combination. These optimal strategy combinations can be provided the useful information in resources allocation for decision makers.