L’aide multicritère à la décision (AMCD) vise à faciliter et améliorer la qualité du processus de prise de décision. Les méthodes d’AMCD permettent de traiter les problèmes de choix, rangement et classification. Ces méthodes impliquent généralement la construction d’un modèle. Déterminer les valeurs des paramètres de ces modèles n’est pas aisé. Les méthodes d’apprentissage indirectes permettent de simplifier cette tâche en apprenant les paramètres du modèle de décision à partir de jugements émis par un décideur tels que “l’alternative a est préférée à l’alternative b” ou “l’alternative a doit être classifiée dans la meilleure catégorie”. Les informations données par le décideur sont généralement parcimonieuses. Le modèle d’AMCD est appris au cours d’un processus interactif entre le décideur et l’analyste. L’analyste aide le décideur à formuler et revoir ses jugements si nécessaire. Le processus s’arrête une fois qu’un modèle satisfaisant les préférences du décideur a été trouvé. Le “preference learning” (PL) est un sous domaine du “machine learning” qui s’intéresse à l’apprentissage des préférences. Les algorithmes de ce domaine sont capables de traiter de grands jeux de données et sont validés au moyen de jeux de données artificiels et réels. Les jeux de données traités en PL sont généralement collectés de différentes sources et sont entachés de bruit.Contrairement à l’AMCD, il existe peu ou pas d’interaction avec l’utilisateur en PL. Le jeu de données fourni en entrée à l’algorithme est considéré comme un échantillon éventuellement bruité d’une “réalité” ou “vérité de terrain”. Les algorithmes utilisés dans ce domaine ont des propriétés statistiques fortes leur permettant de s’affranchir du bruit dans ces jeux de données. Dans cette thèse, nous développons des algorithmes d’apprentissage permettant d’apprendre lesparamètres de modèles d’AMCD. Plus précisément, nous développons une métaheuristique afin d’apprendre les paramètres d’un modèle appelé MR-Sort (“majority rule sorting”). Cette métaheuristique est testée sur des jeux de donnéesartificiels et réels utilisés dans le domaine du PL. Nous utilisons cet algorithme afin de traiter un problème concret dans le domaine médical. Ensuite nous modifions la métaheuristique afin d’apprendre les paramètres d’un modèle plus expressif appelé NCS (“non-compensatory sorting”). Finalement, nous développons un nouveau type de règle de veto pour les modèles MR-Sort et NCS qui permet de prendre les coalitions de critères en compte. La dernière partie de la thèse introduit les méthodes d’optimisation semi-définie positive (SDP) dans le contexte de l’aide multicritère à la décision. Précisément, nous utilisons l’optimisation SDP afin d’apprendre les paramètres d’un modèle de fonction de valeur additive. / Multiple-criteria decision analysis (MCDA) aims at providing support in order to make a decision. MCDA methods allow to handle choice, ranking and sorting problems. These methods usually involve the elicitation of models. Eliciting the parameters of these models is not trivial. Indirect elicitation methods simplify this task by learning the parameters of the decision model from preference statements issued by the decision maker (DM) such as “alternative a is preferred to alternative b” or “alternative a should be classified in the best category”. The information provided by the decision maker are usually parsimonious. The MCDA model is learned through an interactive process between the DM and the decision analyst. The analyst helps the DM to modify and revise his/her statements if needed. The process ends once a model satisfying the preferences of the DM is found. Preference learning (PL) is a subfield of machine learning which focuses on the elicitation of preferences. Algorithms in this subfield are able to deal with large data sets and are validated withartificial and real data sets. Data sets used in PL are usually collected from different sources and aresubject to noise. Unlike in MCDA, there is little or no interaction with the user in PL. The input data set is considered as a noisy sample of a “ground truth”. Algorithms used in this field have strong statistical properties that allow them to filter noise in the data sets.In this thesis, we develop learning algorithms to infer the parameters of MCDA models. Precisely, we develop a metaheuristic designed for learning the parameters of a MCDA sorting model called majority rule sorting (MR-Sort) model. This metaheuristic is assessed with artificial and real data sets issued from the PL field. We use the algorithm to deal with a real application in the medical domain. Then we modify the metaheuristic to learn the parameters of a more expressive model called the non-compensatory sorting (NCS) model. After that, we develop a new type of veto rule for MR-Sort and NCS models which allows to take criteria coalitions into account. The last part of the thesis introduces semidefinite programming (SDP) in the context of multiple-criteria decision analysis. We use SDP to learn the parameters of an additive value function model.

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

分析層級程序法在產品刪除決策之應用 / The recent explosion of product management in consumer packaged goods has highlighted the importance of product assortment decisions. In particular, firms are increasingly faced with the decision of which products to delete from distribution. Upon reflection, there are both strategic and tactical dimensions to this decision. Strategic approaches focus on the development of optimal product assortments as the basis for deletion decisions. Tactical approaches address incremental (i.e., item-by- item) decisions whether to delete any product, and if so, which product. This thesis focuses on tactical approaches and proposes using Analytic Hierarchy Process (AHP) as a systematic and analytic tool that helps to quantify the managerial judgments in identifying the candidates for product deletion. Supported by a practical case study, which illustrates how AHP can be beneficial in quantifying both financial and non-financial product performance rankings for managers’ easier understanding and higher transparency of product deletion decision-making.

Conflict analysis and game theory models are applied to a case study in the upper Rio Grande river basin. The objective is to find which theory best describes past developments in the Rio Grande river basin and the status quo of water use strategies employed by the players (decision makers). By assuming that these past properties will propagate in the future, the preferable change in the equilibrium solution is derived under climate fluctuation, coupled with future population growth scenarios. Past and future Rio Grande resource allocation conflicts are analyzed using (1) multicriterion decision making (MCDM) techniques, such as distance based approach of compromise programming and outranking technique of the ELECTRE family and (2) voting scheme approach of game theory. MCDM and game theory model cases are classified according to the following categories: 1. If decision makers consider each other payoff or if an authority above forces them to consider each other's payoffs, then the conflict analysis problem is a multiactor/ multiobjective problem. 2. If decision makers only care about their own payoff and not what other players payoff are, then the conflict analysis problem is described and solved by game theoretic models. Fifteen decision makers from the Rio Grande water allocation and water management conflict are used as an example to present the different approaches to conflict modeling. From the MCDM techniques used, namely the compromise programming of distance-based approach and the ELECTRE family of outranking relation, the former method stands out as being the most flexible and comprehensive methodology. Though these two methods are conceptually different, for this case study, both methods give approximately the same results. For the game theory analysis, the special voting scheme stands out as being the preferred approach because it better reflects the decision maker's preference and it also is easy to implement and apply. Finally, the climate change scenarios are considered, the 1XCO₂ and the 2XCO₂. Results obtained from these two scenarios indicate the Rio Grande river will face extreme water shortages that will require the development of a different set of water release rules.

The subject of the diploma paper is Multiple Criteria Decision Making of Stocks Traded on Prague Stock Exchange during financial crisis in the years 2008 and 2009. Diploma paper is divided into two sections. First section mainly focus on introduction of multiple criteria decision algorithms and fields, where are algorithms applied. Main purpose of second part of the diploma paper is to compile classified semence of stocks based on fundamental investment principals and make comparison of various orders based on both years and each algorithms.

Decision making is an inherent part of human life. Every day we decide on little things, but also some more complex problems may appear. In such cases, we need to choose a more complex process leading to the final decision. To do so, many multiple-criteria decision-making methods can be used. These methods will be explored in this thesis. They will be used to select accident insurance according to the preferences and requirements of several respondents. Accident insurance protects the insured person against the impairment of their life caused by the consequences of their injury. Accident insurance is a commitment for many years, so its choice needs close attention. The choice of the insurance can be assessed based on of several criteria. Designing a model of multi-criteria decision-making strategy was the main goal of this diploma thesis. The thesis is divided into two parts - the theoretical and practical part. Theoretical part defines the concepts of decision making, multi-criteria decision making and its methods using specialized literature. It also defines the concept of insurance and its specifics relating to accident insurance. The practical part focuses on the specific solution of the given problem. The first step was a survey of offers of insurance companies operating on the Czech market that have separate accident insurance in their product portfolio. Based on these offers, decision variants have been created. The second step was to determine the five criteria on whose basis the variants were evaluated. After the general procedure has been established, the model has been applied. The proposed procedure was tried on a group of respondents to select the best offer for them. The target group, for which the procedure was designed, was set for people between the ages of 40 and 50 who do not have a risky job and do not engage in any hazardous leisure activities. Their preferences were determined by a questionnaire, based on which the decision matrices and weightings of the individual criteria were compiled. The optimal option was recommended to respondents.

Zhong-Yao Zhu. / "6th August 2002." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (p. 227-239). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

A Internet das coisas é constituída de objetos que possuem pequenos sensores e atuadores capazes de interagir com o ambiente. Tais objetos ou coisas estão interconectados entre si e com acesso à Internet por meio de redes com e sem fio. A combinação entre os dispositivos embarcados com sensores e o acesso à Internet possibilita a comunicação dos recursos do mundo físico com o espaço cibernético, desempenhando um papel fundamental na resolução de muitos desafios encontrados na sociedade atual. Porém, a maioria das aplicações existentes são dedicadas a resolver problemas específicos utilizando tais recursos apenas em redes internas, limitando a real capacidade da Internet das Coisas. Diversos trabalhos na literatura propõem a reutilização de tais recursos em forma de serviço por meio de modelos como Dados como Serviço e Sensoriamento como Serviço. Neste contexto, em que potencialmente milhares de recursos podem transferir dados semelhantes de aplicações diferentes, a utilização de técnicas que possam selecionar recursos de forma sensível a contexto torna-se imprescindível. Nesta tese são propostos um conjunto de métodos para melhorar a relação custo-benefício na seleção de recursos em ambientes IoT, auxiliando na tomada de decisão durante a seleção dos recursos que serão ofertados como serviço. Os resultados obtidos por meio de estudos de caso, permitiram a comparação da qualidade da solução e do custo computacional das técnicas aplicadas na seleção de recursos em ambientes IoT, bem como o desenvolvimento de duas novas técnicas para a seleção de recursos, denominadas Elimination Sort e Fast Elimination Sort. / The Internet of Things is composed of objects which have small sensors and actuators capable of interacting with the environment. Such objects or things are interconnected with each other and has access to the Internet through wired and wireless networks. The combination of embedded devices with sensors and access to the Internet become it possible to communicate the resources of the physical world with the cyberspace, playing a key role in solving many challenges found in todays society. However, most existing applications solves a specific problem using its resources just for own purpose, limiting the actual ability of the Internet of Things. Several works propose the reuse of such resources through service models such as Data as Service and Sensing as a Service. In this context, where thousands of resources can transfer similar data from different applications, the use of techniques that can select these features in a context-sensitive way becomes essential. In this thesis, a set of methods to improve the cost-benefit of the process of selection of resources in IoT environments is proposed to support the decision making during resource selection that will be offered as a service. The results obtained through a case study allowed the comparison of the solution quality and the computational cost of the techniques applied for resource selection in IoT environments, as well as the development of two new techniques for the selection of resources called Elimination Sort and Fast Elimination Sort.

Man, Chi Yan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 38-41). / Abstracts in English and Chinese. / Chapter Chapter 1: --- Introduction --- p.1 / Difficult goals in multiple-goal context --- p.1 / Multiple-goal achievement as a complex task --- p.2 / Moderating effect of cognitive flexibility --- p.4 / Moderating effect of multiple-goal efficacy --- p.5 / The model --- p.6 / Chapter Chapter 2: --- Study 1 --- p.8 / Method --- p.8 / Participants --- p.8 / Procedures --- p.8 / Measures --- p.8 / Analysis --- p.10 / Model testing --- p.12 / Hypotheses testing --- p.13 / Discussion --- p.14 / Chapter Chapter 3: --- Study 2 --- p.19 / Method --- p.19 / Participants --- p.19 / Task --- p.19 / Procedures --- p.22 / Measures --- p.23 / Analysis --- p.25 / Manipulation checks and other data inspection --- p.25 / Hypotheses testing --- p.32 / Discussion --- p.32 / Chapter Chapter 4: --- General discussion --- p.34 / Limitation --- p.34 / Implications --- p.35 / Conclusion --- p.37 / References --- p.38 / Appendix A --- p.42 / Appendix B --- p.43

Orientador: Valério Antonio Pamplona Salomon / Banca: Claudemir Leif Tramarico / Banca: Claudio Luis Piratelli / Resumo: A implantação do Balanced Scorecard (BSC) pode criar um diferencial competitivo em Instituição de Ensino Superior (IES). O estudo presente tem por objetivo a utilização de análise multicritério para realização de priorização das perspectivas do BSC em três instituições de ensino superior, administradas pela mesma Mantenedora. Levando-se em consideração que o BSC não possui medição de suas perspectivas em escala de importância, fato esse que pode atrapalhar os gestores durante a implantação, nesse trabalho é possível verificar a utilização do método AHP (Analytic Hierarchy Process), na tomada de decisões com múltiplos critérios, o que permitiu a realização da priorização de perspectivas do BSC em cada uma das IES. Assim, as Instituições de Ensino poderão realizar a implantação do BSC de acordo com o grau de importância das perspectivas na visão de seus Diretores. Por meio dessa pesquisa, foi possível realizar uma análise com a utilização de duas importantes ferramentas: o BSC e o AHP na gestão das Instituições, o que permiti aos Diretores uma melhor condição na preparação e melhor monitoramento dos indicadores estratégicos. / Abstract: The Balanced Scorecard (BSC) deployment can create a competitive differential in Higher Education Institution (HEI). The purpose of this study is to use a multicriteria analysis to prioritize the perspectives of BSC in three higher education institutions, managed by the same maintainer. Considering that the BSC does not have a measurement of its perspectives in scale of importance, which can hinder managers during implantation, in this work it is possible to verify the use of the AHP (Analytic Hierarchy Process) method of making decision with multiple criteria, which allowed the achievement of the prioritization of BSC perspectives in each HEI. Thus, the Educational Institutions may carry out the implementation of the BSC according to the degree of importance of the perspectives in the vision of its Principals. Through this research, it was possible to carry out an analysis with the use of two important tools: the BSC and the AHP in the management of the Institutions, which will allow the Principals a better condition in the preparation and better monitoring of the indicators strategic. / Mestre