Résolution des problèmes de décision de groupe par analyse bipolaire

On entend par décision de groupe ici, la sélection par plusieurs décideurs, d’une ou plusieurs alternatives dans un ensemble vaste d’alternatives. Du fait de l’existence de plusieurs acteurs, le processus de décision doit tenir compte des relations d’influence (positive ou négative) qui peuvent exister entre les acteurs de la décision. De même, l’évaluation des alternatives par rapport aux objectifs des décideurs doit se faire en considérant plusieurs critères ou attributs caractérisant ces alternatives positivement ou négativement. Cette dualité, que ce soit au niveau des relations entre décideurs ou au niveau des relations entre attributs caractérisant les alternatives et les objectifs, est prise en compte dans ce papier à travers la notion de bipolarité. Ainsi, les relations entre décideurs seront évaluées à travers des mesures de concordance et de discordance et les relations entre attributs et objectifs à travers les notions de supportabilité et de rejetabilité. Au final, pour chaque décideur une alternative sera évaluée, par deux mesures ; une mesure de sélectabilité qui agrège les aspects positifs de l’alternative et une mesure de rejetabilité qui agrège les aspects négatifs dans le formalisme des jeux satisfaisants. Un processus de recherche de consensus entre décideurs est proposé pour aboutir à une solution finale dans le cas où aucune alternative ne satisfait simultanément tous les décideurs

A Kind of Risk-Sensitive Group Decision-Making Based on MDP

Abstract. One-switch utility function is used to describe how the risk attitude of a decision maker changes with his wealth level. In this paper additive decision rule is used for the aggregation of decision member's utility which is represented by one-switch utility function. Based on Markov decision processes (MDP) and group utility, a dynamic, multi-stages and risk sensitive group decision model is proposed. The proposed model augments the state of MDP with wealth level, so the policy of the model is defined as an action executed in a state and a wealth level interval. A backward-induction algorithm is given to solve the optimal policy for the model. Numerical examples show that personal risk attitude has a great influence on group decision-making when personal risk attitudes of members are different, while the weights of members play a critical role when personal risk attitudes of members are similar

Distance-based consensus models for fuzzy and multiplicative 3 preference relations

This paper proposes a distance-based consensus model for fuzzy preference relations where the weights of fuzzy preference relations are automatically determined. Two indices, an individual to group consensus index (ICI) and a group consensus index (GCI), are introduced. An iterative consensus reaching algorithm is presented and the process terminates until both the ICI and GCI are controlled within predefined thresholds. The model and algorithm are then extended to handle multiplicative preference relations. Finally, two examples are illustrated and comparative analyses demonstrate the effectiveness of the proposed methods

Influence Analysis in Consensus Search - A Multi Criteria Group Decision Making Approach in Environmental Management

The environmental decision problems often are divisive, even in a technical realm, decision makers with strong personalities influence outcomes. The purpose of this study is to define and quantify the factors that affect the conservation objectives of a national natural park located in Colombia, South America adding the judgments of six decision makers with different knowledge (every decision maker is also a stakeholder representative). This paper uses a hybrid multiple criteria group decision making model (MCDM), combining the social network analysis (SNA), analytic hierarchy process (AHP) and similarity measures to solve the consensus and anchoring problem among environmental decision makers. The SNA technique is used to build an influential network relation map among decision makers and to obtain their weights for applying a weighted analytic hierarchy process. Then, the final decision matrices for every decision maker are compared between them in order to identify the consensus level of the problem.Romero Gelvez, JI.; García Melón, M. (2016). Influence Analysis in Consensus Search - A Multi Criteria Group Decision Making Approach in Environmental Management. International Journal of Information Technology and Decision Making. 15(4):791-813. doi:10.1142/S0219622016400034S791813154Regan, H. M., Colyvan, M., & Markovchick-Nicholls, L. (2006). A formal model for consensus and negotiation in environmental management. Journal of Environmental Management, 80(2), 167-176. doi:10.1016/j.jenvman.2005.09.004Reed, M. S. (2008). Stakeholder participation for environmental management: A literature review. Biological Conservation, 141(10), 2417-2431. doi:10.1016/j.biocon.2008.07.014Gomez-Navarro, T., & Garcia-Melon, M. (2011). DESIGN OF AN EFFICIENCY INDEX FOR THE RANK ORDER OF SOIL REMEDIATION TECHNIQUES. Environmental Engineering and Management Journal, 10(5), 603-613. doi:10.30638/eemj.2011.083Aragonés-Beltrán, P., García-Melón, M., & Estruch-Guitart, V. (2015). ANALYSIS OF THE PARTICIPATION OF STAKEHOLDERS IN ENVIRONMENTAL MANAGEMENT BASED ON ANP: APPLICATION TO A SPANISH NATURAL PARK. International Journal of the Analytic Hierarchy Process, 7(1). doi:10.13033/ijahp.v7i1.276Belton, V., & Stewart, T. J. (2002). Multiple Criteria Decision Analysis. doi:10.1007/978-1-4615-1495-4Ginevičius, R., & Podvezko, V. (2009). EVALUATING THE CHANGES IN ECONOMIC AND SOCIAL DEVELOPMENT OF LITHUANIAN COUNTIES BY MULTIPLE CRITERIA METHODS. Technological and Economic Development of Economy, 15(3), 418-436. doi:10.3846/1392-8619.2009.15.418-436Ramzan, N., Degenkolbe, S., & Witt, W. (2008). Evaluating and improving environmental performance of HC’s recovery system: A case study of distillation unit. Chemical Engineering Journal, 140(1-3), 201-213. doi:10.1016/j.cej.2007.09.042Sólnes, J. (2003). Environmental quality indexing of large industrial development alternatives using AHP. Environmental Impact Assessment Review, 23(3), 283-303. doi:10.1016/s0195-9255(03)00004-0Beccali, M., Cellura, M., & Mistretta, M. (2003). Decision-making in energy planning. Application of the Electre method at regional level for the diffusion of renewable energy technology. Renewable Energy, 28(13), 2063-2087. doi:10.1016/s0960-1481(03)00102-2Varvasovszky, Z. (2000). A stakeholder analysis. Health Policy and Planning, 15(3), 338-345. doi:10.1093/heapol/15.3.338Prell, C., Hubacek, K., & Reed, M. (2009). Stakeholder Analysis and Social Network Analysis in Natural Resource Management. Society & Natural Resources, 22(6), 501-518. doi:10.1080/08941920802199202Charnley, S., & Engelbert, B. (2005). Evaluating public participation in environmental decision-making: EPA’s superfund community involvement program. Journal of Environmental Management, 77(3), 165-182. doi:10.1016/j.jenvman.2005.04.002Reed, M. S., Graves, A., Dandy, N., Posthumus, H., Hubacek, K., Morris, J., … Stringer, L. C. (2009). Who’s in and why? A typology of stakeholder analysis methods for natural resource management. Journal of Environmental Management, 90(5), 1933-1949. doi:10.1016/j.jenvman.2009.01.001Bonner, B. L., & Bolinger, A. R. (2013). Separating the confident from the correct: Leveraging member knowledge in groups to improve decision making and performance. Organizational Behavior and Human Decision Processes, 122(2), 214-221. doi:10.1016/j.obhdp.2013.07.005Kirchler, E., & Davis, J. H. (1986). The influence of member status differences and task type on group consensus and member position change. Journal of Personality and Social Psychology, 51(1), 83-91. doi:10.1037/0022-3514.51.1.83Sniezek, J. A., & Henry, R. A. (1989). Accuracy and confidence in group judgment. Organizational Behavior and Human Decision Processes, 43(1), 1-28. doi:10.1016/0749-5978(89)90055-1Bonner, B. L., Sillito, S. D., & Baumann, M. R. (2007). Collective estimation: Accuracy, expertise, and extroversion as sources of intra-group influence. Organizational Behavior and Human Decision Processes, 103(1), 121-133. doi:10.1016/j.obhdp.2006.05.001Burgman, M. (2005). Risks and Decisions for Conservation and Environmental Management. doi:10.1017/cbo9780511614279Mitchell, R. K., Agle, B. R., & Wood, D. J. (1997). Toward a Theory of Stakeholder Identification and Salience: Defining the Principle of who and What Really Counts. Academy of Management Review, 22(4), 853-886. doi:10.5465/amr.1997.9711022105Bryson, J. M. (2004). What to do when Stakeholders matter. Public Management Review, 6(1), 21-53. doi:10.1080/14719030410001675722Biggs, S., & Matsaert, H. (1999). An actor-oriented approach for strengthening research and development capabilities in natural resource systems. Public Administration and Development, 19(3), 231-262. doi:10.1002/(sici)1099-162x(199908)19:33.0.co;2-eWu, J., & Chiclana, F. (2014). A social network analysis trust–consensus based approach to group decision-making problems with interval-valued fuzzy reciprocal preference relations. Knowledge-Based Systems, 59, 97-107. doi:10.1016/j.knosys.2014.01.017Sabidussi, G. (1966). The centrality index of a graph. Psychometrika, 31(4), 581-603. doi:10.1007/bf02289527Chiclana, F., Tapia García, J. M., del Moral, M. J., & Herrera-Viedma, E. (2013). A statistical comparative study of different similarity measures of consensus in group decision making. Information Sciences, 221, 110-123. doi:10.1016/j.ins.2012.09.014Wu, J., Chiclana, F., & Herrera-Viedma, E. (2015). Trust based consensus model for social network in an incomplete linguistic information context. Applied Soft Computing, 35, 827-839. doi:10.1016/j.asoc.2015.02.023Xu, J., & Wu, Z. (2011). A discrete consensus support model for multiple attribute group decision making. 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Consensus measure with multi-stage fluctuation utility based on China’s urban demolition negotiation

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Utility functions are often used to reflect decision makers' (DMs') preferences. They have the following two merits: one refers to the representation of the DM's utility (satisfaction) level, the other one to the measuring of the consensus level in a negotiation process. Taking the background of China's urban house demolition, a new kind of consensus model is established by using di erent types of multi-stage fluctuation utility functions, such as concave, convex, S-shaped, reversed S-shaped, reversed U-shaped as well as their combinations, to reveal negotiators' dynamic physiological preferences and consensus level. Moreover, the eff ects of budget and the individual compensation tolerance on the consensus level are also discussed with previous research, the proposed model takes both the negotiation cost and DM's consideration, and most importantly, it is computational less complex

A self-management mechanism for non-cooperative behaviors in large-scale group consensus reaching processes

In large-scale group decision making (GDM), non-cooperative behavior in the consensus reaching process (CRP) is not unusual. For example, some individuals might form a small alliance with the aim to refuse attempts to modify their preferences or even to move them against consensus to foster the alliance’s own interests. In this paper, we propose a novel framework based on a self-management mechanism for non-cooperative behaviors in large-scale consensus reaching processes (LCRPs). In the proposed consensus reaching framework, experts are classified into different subgroups using a clustering method, and experts provide their evaluation information, i.e., the multi-criteria mutual evaluation matrices (MCMEMs), regarding the subgroups based on subgroups’ performance (e.g., professional skills, cooperation, and fairness). The subgroups’ weights are dynamically generated from the MCMEMs, which are in turn employed to update the individual experts’ weights. This self-management mechanism in the LCRP allows penalizing the weights of the experts with non-cooperative behaviors. Detailed simulation experiments and comparison analysis are presented to verify the validity of the proposed framework for managing non-cooperative behaviors in the LCRP

Multicriteria methodology for decoupling point placement under production postponement strategy

The accelerated growth of global markets and the increased bargaining power of customers, has generated a highly competitive environment with a lot of risks for manufacturing companies. In response, the literature has shown mass customization and, in particular way, the postponement strategy as new paradigms of production that allows offering simultaneously high levels of flexibility and efficiency to consumers. Regarding this issue, the decoupling point location is positioned as the most important decision in the implementation of postponement. Starting from the importance of this topic and from a review of the state of the art, it was detected the need to develop a methodology to locate the decoupling point, by integrating qualitative and quantitative criteria and that additionally allows the participation of panel of experts. Thereby, this thesis shows the development of a new multi-criteria methodology; which consists of 7 steps that allow locating the decoupling point, in a production system, according to the needs of the system and relying on the experience and knowledge of experts. Additionally, in order to validate the performance of the methodology in real cases, two study cases developed in the companies Herragro S.A. and Muebles Marco Gomez, are presentedResumen: El crecimiento acelerado de los mercados globalizados y el aumento del poder de negociación de los clientes, ha generado un ambiente fuertemente competitivo y con gran cantidad de riesgos para las empresas manufactureras. Como respuesta, la literatura ha mostrado a la personalización masiva y, de forma particular a la estrategia de aplazamiento como nuevos paradigmas de la producción que permiten ofrecer a los clientes de forma simultánea altos niveles de flexibilidad y eficiencia. Frente a este tema la ubicación del punto de desacople se posiciona como la decisión más importante en la implementación del aplazamiento. Partiendo de la importancia de este tópico y de una revisión del estado del arte, se detecta la necesidad de desarrollar una metodología que permita ubicar el punto de desacople integrando criterios cualitativos y cuantitativos y que adicionalmente permita la participación de grupos de expertos. De esta forma, la presente tesis muestra el desarrollo de una nueva metodología multicriterio; la cual está conformada por 7 pasos que permiten ubicar el punto de desacople, en un sistema de producción, acorde con las necesidades del sistema y apoyándose de la experiencia y conocimiento de los expertos. Adicionalmente, y con el objetivo de validar el funcionamiento de la metodología en casos reales, se presentan dos casos de estudio desarrollados en las empresas Herragro S.A y Muebles Marco GómezMaestrí

Structuration des processus d'aide à la décision par analyse bipolaire

Le travail de recherche présenté dans ce mémoire s'inscrit dans le champ de l'aide à la décision multicritère. Ce champ aborde la décision dans un contexte où un groupe d'alternatives est évalué à travers un ensemble de critères (souvent contradictoires) afin d'estimer le potentiel de chacune à atteindre les objectifs fixés par un certain nombre de décideurs. La contribution de cette thèse concerne la structuration des problèmes d'aide à la décision par une approche bipolaire flexible qui permet d'évaluer les alternatives en distinguant leurs aspects positifs et négatifs vis-à-vis des objectifs à atteindre. Dans un premier temps, des modèles de structuration bipolaire sont proposés pour évaluer les problèmes de décision au niveau individuel. Les relations de synergie et les interactions potentielles entre les caractéristiques de la décision (attributs, alternatives, objectifs) sont modélisées dans un contexte bipolaire et intégrées à des approches de résolution tenant compte de l'environnement certain ou incertain dans lequel l'évaluation se déroule. Dans un deuxième temps, les décisions de groupe sont traitées en considérant l'impact du facteur humain (à travers les notions de peur, individualisme, influence, prudence, etc.) sur la capacité décisionnelle aux niveaux individuel et collectif. Des modèles d'évaluation et des techniques d'atteinte de consensus sont proposées pour deux catégories de problèmes relativement indépendants ; les problèmes de choix social et les jeux stratégiques.The research presented in this thesis concerns the multi-criteria decision support field. This field aims at helping decision makers (DM) to face decisions involving several conflicting objectives. To deals with this, decision is addressed in a context where a group of alternatives is evaluated through a set of criteria (often contradictory) to estimate the potential of each to achieve the goals. The main concern of this research is to propose flexible structuring decision problem support for evaluating alternatives distinguishing between positive and negative aspects they present with regard to objectives achievement. Bipolar structure models are proposed first to evaluate the decision problems at the individual level. The synergistic relationships and potential interactions between the decision characteristics (attributes, alternative objectives) are modeled in a bipolar context and integrated into resolution approaches taking account the certain or uncertain environment in which the evaluation takes place. In a second part, group decision problems are discussed taking into account the impact of human behaviour (influence, individualism, fear, caution, etc.) on decisional capacity at individual and collective levels. Valuation models and a consensus process are proposed in two relatively independent problem categories: social choice problems, and, strategic game problems

Sistema multiagente para modelar procesos de consenso en toma de decisión en grupo a gran escala usando técnicas de soft computing

[ES]La presente Tesis se centra en el campo de los Procesos de Alcance de Consenso en Toma de Decisión en Grupo. En la literatura se han propuesto diversos modelos y enfoques para dar soporte a dichos procesos en problemas de toma de decisión en grupo reales, los cuales normalmente se han centrado en pequeños grupos de expertos. Sin embargo, dichos modelos presentan algunas dificultades:::;. y limitaciones para la gestión de grandes grupos. Dado que los problemas de toma de decisión en grupo a gran escala, en los que participa un elevado número de expertos, están cobrando una relevancia cada vez mayor en múltiples entornos tecnológicos, en esta investigación se propone un Sistema Multiagente basado en técnicas de soft computing, capaz de dar soporte en procesos de negociación semisupervisados, para alcanzar el consenso en problemas reales en los que participa un elevado número de expertos.[EN]This thesis focuses on the field of Consensus Reaching Processes within Group Decision Making. Several models and approaches have been proposed in the literature to support such processes in reallife group decision making problems, which have normally focused on small groups of experts. However, such models present some difficulties and limitations for the management of large groups. Due to the fact that large-scale group decision making problems, in which a large number of experts participate, are attaining an increasing relevance in multiple technological environments, this research proposes a multiagent system based on soft computing techniques, capable of giving support to semi-supervised negotiation processes in order to reach consensus in real-life problems in which a large number of experts take partoTesis Univ. Jaén. Departamento de Informática, leída el 25 de febrero de 201