In this study two different hybrid ranking approaches based on data envelopment analysis and outranking relations for ranking alternatives are proposed. Outranking relations are widely used in Multicriteria Decision Making (MCDM) for ranking the alternatives and appropriate in situations when we have limited information on the preference structure of the decision maker. Yet to apply these methods DM should provide exact values for method parameters (weights, thresholds etc.) as well as basic information such as alternative scores. DEA is used for classification of decision making units according to their efficiency scores in a non-parameteric way. The proposed hybrid approaches utilize PROMETHEE (a well known method based on outranking relations) to construct outranking relations by pairwise comparisons and a technique similar to DEA crossefficiency ranking for aggregating comparisons. While first of the proposed approaches can deal with imprecise specification of criterion weights, second approach can utilize imprecise weights and thresholds.

abstract: Life Cycle Assessment (LCA) quantifies environmental impacts of products in raw material extraction, processing, manufacturing, distribution, use and final disposal. The findings of an LCA can be used to improve industry practices, to aid in product development, and guide public policy. Unfortunately, existing approaches to LCA are unreliable in the cases of emerging technologies, where data is unavailable and rapid technological advances outstrip environmental knowledge. Previous studies have demonstrated several shortcomings to existing practices, including the masking of environmental impacts, the difficulty of selecting appropriate weight sets for multi-stakeholder problems, and difficulties in exploration of variability and uncertainty. In particular, there is an acute need for decision-driven interpretation methods that can guide decision makers towards making balanced, environmentally sound decisions in instances of high uncertainty. We propose the first major methodological innovation in LCA since early establishment of LCA as the analytical perspective of choice in problems of environmental management. We propose to couple stochastic multi-criteria decision analytic tools with existing approaches to inventory building and characterization to create a robust approach to comparative technology assessment in the context of high uncertainty, rapid technological change, and evolving stakeholder values. Namely, this study introduces a novel method known as Stochastic Multi-attribute Analysis for Life Cycle Impact Assessment (SMAA-LCIA) that uses internal normalization by means of outranking and exploration of feasible weight spaces. / Dissertation/Thesis / M.S. Civil and Environmental Engineering 2013

Multiple-criteria decision-making (MCDM) is a field of decision theory concerned with analyzing discrete sets of variables evaluated by multiple criteria. Facilitating decisions in such situations are several methods, among them a family known as ELECTRE. Using threshold values and the concept of outranking, they allow for improved modeling of the uncertain nature of real systems. This thesis sets out to describe all of the basic ELECTRE methods, as well as several of their modifications and further extensions and aims to do so with a sufficient level of detail and using precise mathematical language. It also presents key applications of said methods and reviews their implementation in software. Lastly, it introduces a brand new software, ELIA, developed as a part of the thesis. It allows users to solve practical problems using four of the basic ELECTRE methods.

abstract: Comparative life cycle assessment (LCA) evaluates the relative performance of multiple products, services, or technologies with the purpose of selecting the least impactful alternative. Nevertheless, characterized results are seldom conclusive. When one alternative performs best in some aspects, it may also performs worse in others. These tradeoffs among different impact categories make it difficult to identify environmentally preferable alternatives. To help reconcile this dilemma, LCA analysts have the option to apply normalization and weighting to generate comparisons based upon a single score. However, these approaches can be misleading because they suffer from problems of reference dataset incompletion, linear and fully compensatory aggregation, masking of salient tradeoffs, weight insensitivity and difficulties incorporating uncertainty in performance assessment and weights. Consequently, most LCA studies truncate impacts assessment at characterization, which leaves decision-makers to confront highly uncertain multi-criteria problems without the aid of analytic guideposts. This study introduces Stochastic Multi attribute Analysis (SMAA), a novel approach to normalization and weighting of characterized life-cycle inventory data for use in comparative Life Cycle Assessment (LCA). The proposed method avoids the bias introduced by external normalization references, and is capable of exploring high uncertainty in both the input parameters and weights. / Dissertation/Thesis / Doctoral Dissertation Civil and Environmental Engineering 2015

A escolha por fazer ou por comprar é um problema clássico enfrentado pelas empresas. Essa decisão diz respeito à opção de fazer internamente, optar por uma gestão hibrida (interna e externa ao mesmo tempo) ou terceirizar uma atividade. Por envolver diversos critérios, muitos responsáveis por ela utilizam métodos de decisão multicritério para que se obtenha melhores resultados. O objetivo deste trabalho consiste em desenvolver uma estrutura para a tomada de decisão de fazer ou comprar e utilizar métodos de decisão multicritério para conferir maior confiabilidade à essa decisão. Para isso, os objetivos específicos são: (1) realizar uma pesquisa bibliográfica sobre o tema (decisão de fazer ou comprar auxiliada por métodos de decisão multicritério), (2) propor um processo estruturado de decisão para o problema de fazer ou comprar, (3) propor métodos adequados aos propósitos de categorização ou ordenação nas diferentes etapas do processo, incluindo métodos que contemplem a possibilidade de decisão em grupo e (4) realizar um estudo comparativo de métodos de decisão multicritério para a decisão sobre Fazer ou Comprar. Os objetivos desse trabalho foram plenamente alcançados trazendo contribuições como: uma revisão bibliográfica sistemática sobre métodos de decisão multicritério para o problema de fazer ou comprar; uma estrutura de decisão para dar suporte à decisão de fazer ou comprar; a aplicação de métodos ainda não utilizados para o problema de fazer ou comprar; aplicação de métodos que suportem a problemática da decisão em grupo e; a comparação entre dois métodos para o propósito de categorização e duas para o propósito de ordenação. / The make or buy decision is a classical decision problem in operations management and it is difficult to make because of its very nature (multiple criteria). To better contend with these challenges, many decision makers choose Multi-Criteria Decision Making (MCDM) techniques to support their decisions. The aim of this work is to develop a methodology to support the make or buy decision and the use of the multi-criteria decision methods in this context. The specific objectives are: (1) to conduct a literature research about multi-criteria decision making techniques to support the make or buy decision; (2) to propose a structured decision framework to the make or buy problem; (3) to propose appropriate methods for categorization or ordering at different stages of the process, including methods that support group decisions and; (4) to perform a comparative study of multi-criteria decision-making methods for the make or buy problem. The objectives of this work were fully achieved by bringing contributions such as: a systematic literature review on multi-criteria decision-making methods for the make or buy problem; A decision framework to support the make or buy decision; The application of methods that were not found in the systematic literature review for the problem of make or buy problem; Application of methods that support the group decision problem and; The comparison between two techniques for categorization purposes and two for ordering purposes.

A escolha por fazer ou por comprar é um problema clássico enfrentado pelas empresas. Essa decisão diz respeito à opção de fazer internamente, optar por uma gestão hibrida (interna e externa ao mesmo tempo) ou terceirizar uma atividade. Por envolver diversos critérios, muitos responsáveis por ela utilizam métodos de decisão multicritério para que se obtenha melhores resultados. O objetivo deste trabalho consiste em desenvolver uma estrutura para a tomada de decisão de fazer ou comprar e utilizar métodos de decisão multicritério para conferir maior confiabilidade à essa decisão. Para isso, os objetivos específicos são: (1) realizar uma pesquisa bibliográfica sobre o tema (decisão de fazer ou comprar auxiliada por métodos de decisão multicritério), (2) propor um processo estruturado de decisão para o problema de fazer ou comprar, (3) propor métodos adequados aos propósitos de categorização ou ordenação nas diferentes etapas do processo, incluindo métodos que contemplem a possibilidade de decisão em grupo e (4) realizar um estudo comparativo de métodos de decisão multicritério para a decisão sobre Fazer ou Comprar. Os objetivos desse trabalho foram plenamente alcançados trazendo contribuições como: uma revisão bibliográfica sistemática sobre métodos de decisão multicritério para o problema de fazer ou comprar; uma estrutura de decisão para dar suporte à decisão de fazer ou comprar; a aplicação de métodos ainda não utilizados para o problema de fazer ou comprar; aplicação de métodos que suportem a problemática da decisão em grupo e; a comparação entre dois métodos para o propósito de categorização e duas para o propósito de ordenação. / The make or buy decision is a classical decision problem in operations management and it is difficult to make because of its very nature (multiple criteria). To better contend with these challenges, many decision makers choose Multi-Criteria Decision Making (MCDM) techniques to support their decisions. The aim of this work is to develop a methodology to support the make or buy decision and the use of the multi-criteria decision methods in this context. The specific objectives are: (1) to conduct a literature research about multi-criteria decision making techniques to support the make or buy decision; (2) to propose a structured decision framework to the make or buy problem; (3) to propose appropriate methods for categorization or ordering at different stages of the process, including methods that support group decisions and; (4) to perform a comparative study of multi-criteria decision-making methods for the make or buy problem. The objectives of this work were fully achieved by bringing contributions such as: a systematic literature review on multi-criteria decision-making methods for the make or buy problem; A decision framework to support the make or buy decision; The application of methods that were not found in the systematic literature review for the problem of make or buy problem; Application of methods that support the group decision problem and; The comparison between two techniques for categorization purposes and two for ordering purposes.

Cloud computing is an emerging trend where clients are billed for services on a pay-per-use basis. Service level agreements define the formal negotiations between the clients and the service providers on common metrics such as processing power, memory and bandwidth. In the case of service level agreement violations, the service provider is penalised. From service provider's point of view, providing cloud services efficiently within the negotiated metrics is an important problem. Particularly, in large-scale data center settings, manual administration for resource allocation is not a feasible option. Service providers aim to maximize resource utilization in the data center, as well as, avoiding service level agreement violations. On the other hand, from the client's point of view, the cloud must continuously ensure enough resources to the changing workloads of hosted application environments and services. Therefore, an autonomous cloud manager that is capable of dynamically allocating resources in order to satisfy both the client and the service provider's requirements emerges as a necessity. In this thesis, we focus on the autonomous resource allocation in cloud computing environments. A distributed resource consolidation manager for clouds, called IMPROMPTU, was introduced in our previous studies. IMPROMPTU adopts a threshold based reactive design where each unique physical machine is coupled with an autonomous node agent that manages resource consolidation independently from the rest of the autonomous node agents. In our previous studies, IMPROMPTU demonstrated the viability of Multiple Criteria Decision Analysis (MCDA) to provide resource consolidation management that simultaneously achieves lower numbers of reconfiguration events and service level agreement violations under the management of three well-known outranking-based methods called PROMETHEE II, ELECTRE III and PAMSSEM II. The interesting question of whether more efficient single synthesizing criterion and outranking based MCDA methods exist was left open for research. This thesis addresses these limitations by analysing the capabilities of IMPROMPTU using a comprehensive set of single synthesizing criterion and outranking based MCDA methods in the context of dynamic resource allocation. The performances of PROMETHEE II, ELECTRE III, PAMSSEM II, REGIME, ORESTE, QUALIFEX, AHP and SMART are investigated by in-depth analysis of simulation results. Most importantly, the question of what denotes the properties of good MCDA methods for this problem domain is answered. / Graduate / 0984

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

No description available.

Cette thèse traite du processus d’évaluation et de sélection de projets sur la base de critères multiples. Outre la capacité du modèle à permettre une identification efficace des meilleurs projets et leur intégration à un portefeuille, l’équité et la transparence sont des considérations importantes dans la conception de modèles d’appui à ce processus. Nous proposons un cadre de travail général pour l’évaluation de projets, Il reprend les codes de l’analyse SWOT, dont de nombreuses organisations orientées projets sont familières. Nos contributions apportent des éléments de réponse à la question de « l’après SWOT », à laquelle ces organisations peuvent éprouver des difficultés à répondre. Dans ce cadre de travail, nous introduisons et discutons un modèle de préférences permettant de mesurer l’importance des critères sur deux dimensions, représentant de manière indépendante leurs capacités de conviction et d’opposition. Suivant l’évaluation et en préalable à la sélection, le filtrage consiste à écarter les projets trop inadéquats. Nous proposons un mécanisme basé sur la dominance pour effectuer cette opération. Nous proposons, enfin, deux méthodes de sélection de projets, chacune étant basée sur une procédure d’agrégation multicritère originale. La première méthode, SPADE (pour Structure de Préférence pour l’Aide à la Décision) est une approche de surclassement, destinée à des contextes où les préférences exprimées concernent essentiellement les projets individuels, et dans lesquels les décisions concernant un projet peuvent être argumentées en référence à des projets tiers. Nous garantissons la validité théorique de SPADE, en amont, ce qui permet un temps de mise en œuvre réduit et une utilisation en temps réel. En pratique, nous illustrons l’application de SPADE, en la comparant à deux autres approches d’aide multicritères à la décision, MAUT et ELECTRE, en mettant en exergue ses spécificités. La seconde méthode, RADAR (Règles d’Aide à la Décision et à l’ARgumentation) est une approche à base de règles logiques. Elle est destinée à des contextes plus contraints dans lesquels les préférences exprimées concernent à la fois les projets individuels, mais aussi le portefeuille de projets (degré de diversification, budget total, etc.). De plus, l'argumentation des décisions est ici basée exclusivement sur la qualité intrinsèque des projets en référence à une norme fixe. RADAR permet également la construction automatique de tels arguments. Nous proposons un programme linéaire en variable mixtes permettant de valider théoriquement cette approche. Cependant, sa résolution est nécessaire à chaque mise en œuvre de RADAR, ce qui limite l’application de cette approche au temps différé. Nous illustrons une telle application sur un jeu de données représentant des évaluations de projets financés par le Fond des Nations Unies pour la Démocratie (UNDEF). / Project portfolio management (PPM) involves the use of methods and tools, allowing an organization to plan, evaluate, analyze and screen the execution of a set of projects or project proposals, sharing common resources or aiming at the attainment of common objectives. Multicriteria decision aid models are useful tools to support this process, given their ability to accurately model preferences, and rationally agregate points of view. However, existing models present some lacks that limit their use outside of academic circles : (i) They neglect the non-symetrical nature of the importance of some criteria that are relevant in PPM. (ii) The black box effect makes it hard to use them for the argumentation of decisions and to gain their acceptance by users (iii) They are implicitly fitted for private/for-profit projects, which limits their use in public organizations. In this thesis, our contribution consists in proposing two multicriteria methods for supporting the activities of evaluating, selecting and arguing decision, for project portfolio management. We propose: (i) An analysis of the specific features of public and private projects and their consequences for decision support (ii) A framework that allows an independent modeling of the abilities of a criterion to oppose and convince (iii) Two transparent multicriteria agregation procedures, fitted for different decision contexts. We ensure the theoretical validity of our approaches and illustrate their applicability on real data, with satisfying results.