Group decision making with incomplete reciprocal preference relations based on multiplicative consistency

This paper comprises a new iterative method for multi-person decision making based on multiplicative consistency with incomplete reciprocal preference relations (IRPRs). Additionally, multiplicative transitivity property of reciprocal preference relation (RPR) is used at the first level to estimate the unknown preference values and get the complete preference relation, then it is confirmed to be multiplicative consistent by using transitive closure formula. Following this, expert's weights are evaluated by merging consistency and trust weights. The consistency weights against the experts are evaluated through multiplicative consistency investigation of the preferences given by each expert, while trust weights play the role to measure the level of trust for an expert. The consensus process determines whether the selection procedure should start or not. If it results in negative, the feedback mechanism is used to enhance the consensus degree. At the end, a numerical example is given to demonstrate the efficiency and practicality of the proposed method

Consistency based completion approaches of incomplete preference relations in uncertain decision contexts.

Uncertainty, hesitation and vagueness are inherent to human beings when articulating opinions and preferences. Therefore in decision making situations it might well be the case that experts are unable to express their opinions in an accurate way. Under these circumstances, various families of preference relations (PRs) have been proposed (linguistic, intuitionistic and interval fuzzy PRs) to allow the experts to manifest some degree of hesitation when enunciating their opinions. An extreme case of uncertainty happens when an expert is unable to differentiate the degree up to which one preference is preferred to another. Henceforth, incomplete preference relations are possible. It is worth to bear in mind that incomplete information does not mean low quality information, on the contrary, in many occasions experts might prefer no to provide information in other to keep consistency. Consequently mechanism to deal with incomplete information in decision making are necessary. This contribution presents the main consistency based completion approaches to estimate incomplete preference values in linguistic, intuitionistic and interval fuzzy PRs

Consistency-driven methodology to manage incomplete linguistic preference relation: A perspective based on personalized individual semantics

The file attached to this record is the author's final peer reviewed version.In linguistic decision making problems there may be cased when decision makers will not be able to provide complete linguistic preference relations. However, when estimating unknown linguistic preference values in incomplete preference relations, the existing research approaches ignore the fact that words mean different things for different people, i.e. decision makers have personalized individual semantics (PISs) regarding words. To manage incomplete linguistic preference relations with PISs, in this paper we propose a consistency-driven methodology both to estimate the incomplete linguistic preference values and to obtain the personalized numerical meanings of linguistic values of the different decision makers. The proposed incomplete linguistic preference estimation method combines the characteristic of the personalized representation of decision makers and guarantees the optimum consistency of incomplete linguistic preference relations in the implementation process. Numerical examples and a comparative analysis are included to justify the feasibility of the PISs based incomplete linguistic preference estimation method

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization 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