Representation and aggregation of crisp and fuzzy ordered structures: applications to social choice

The present memory is structured as follows: after the Introduction, in the Chapter 2 of preliminaries, we will pay attention to the three areas which sustain the development of this thesis. These are, binary relations, Social Choice and Fuzzy sets. Chapter 3 is devoted to the study of fuzzy Arrovian models. First, it is introduced the concept of a fuzzy preference. Next, we define fuzzy aggregation rules and all of the restrictions of common sense, which are inspired by the restrictions that come from the classic Arrovian model. Next, different models are defined in the fuzzy setting. Their definitions depend on the particular nuances and features of a preference (choosing a transitivity type and a connectedness type) and the restrictions on an aggregation function (choosing an independence of irrelevant alternatives property,an unanimity property, etc). Different possibility and impossibility theorems have been proved depending on the set of definition and restrictions. In Chapter 4 it is studied the problem of the decomposition of fuzzy binary relations. There, it is defined clearly the problem of setting suitable decomposition rules. That is, we analyze how to obtain a strict preference and an indifference from the weak preference in a fuzzy approach. In this chapter, the existence and the uniqueness of certain kind of decomposition rules associated to fuzzy unions are characterized. In Chapter 5, the decomposition rules studied in Chapter 4 are used to achieve a new impossibility result. It is important to point out that in the proof of the main result in this chapter it is introduced a new technique. In this proof, fuzzy preferences are framed through an auxiliary tuple of five crisp binary relations, that we name a pseudofuzzy preference. An aggregation model à la Arrow of pseudofuzzy preferences is also studied,but the main result is about the aggregation of fuzzy preferences that come from decompositions.Chapters 3, 4 and 5 constitute the main body of this memory. Then a section of conclusions is included. It contains suggestions for further studies, open problems and several final comments. Finally, an Appendix has been added in order to give an account of the work done within these three years, that can not be included in the body of the present memory.

A novel intuitionistic fuzzy preference relations for multiobjective goal programming problems

This paper investigates novel intuitionistic fuzzy preferences relations to determine the imprecise linguistic terms with fuzzy goals. The proposed intuitionistic fuzzy goal programming (IFGP) considers the degree of vagueness and hesitations simultaneously. Different sorts of membership functions such as linear, exponential, parabolic, and hyperbolic have been introduced to depict the linguistic importance term. The overall satisfaction level is achieved by maximizing the convex combination of each fuzzy goals and the preference relations simultaneously. To verify and validate the proposed IFGP model, a numerical example is presented with the comparative study. Further, it is also applied to a banking financial statement management system problem. The proposed IFGP approach outperforms over others. At last, the conclusion and future research direction are suggested based on the performed study.

The graph model for conflict resolution with consensus fuzzy preferences and its application to environmental sustainable development

Conflict of environmental sustainable development as a common phenomenon can be seen everywhere in life. To capture consensus problems of decision makers (DMs) in conflict, a consensus and non-consensus fuzzy preference relation (FPR) matrix is proposed to the framework of the Graph Model for Conflict Resolution (GMCR). Concentrating on the case of two DMs within GMCR paradigm, four standard fuzzy solution concepts are developed into eight fuzzy stability definitions which can fully represent DMs’ behavior characteristics of win-win and self-interested. To demonstrate how the novel GMCR methodology proposed in this paper can be conveniently utilized in practice, it is then applied to an environmental sustainable development conflict with two DMs. The results show that the general fuzzy equilibrium solutions are the intersection of consensus fuzzy equilibrium and non-consensus fuzzy equilibrium. Therefore, the GMCR technique considering DMs’ consensus can effectively predict the various possible solutions of conflict development under different DMs’ behavior preferences and provide new insights for analysts into a conflict.

Existence of an equilibrium for pure exchange economy with fuzzy preferences

This paper focuses on a new model to reach the existence of equilibrium in a pure exchange economy with fuzzy preferences (PXE-FP). The proposed model integrates exchange, consumption and the agent’s fuzzy preference in the consumption set. We set up a new fuzzy binary relation on the consumption set to evaluate the fuzzy preferences. Also, we prove that there exists a continuous fuzzy order-preserving function in the consumption set under certain conditions. The existence of a fuzzy competitive equilibrium for the PXE-FP is confirmed through a new result on the existence of fuzzy Nash equilibrium for fuzzy non-cooperative games. The payoffs of all strategy profiles for any agent are fuzzy numbers in fuzzy non-cooperative games. Finally, we show that the fuzzy competitive equilibrium could be characterized as a solution to an associated quasi-variational inequality, giving rise to an equilibrium solution.

Decomposition and Arrow-Like Aggregation of Fuzzy Preferences

We analyze the concept of a fuzzy preference on a set of alternatives, and how it can be decomposed in a triplet of new fuzzy binary relations that represent strict preference, weak preference and indifference. In this setting, we analyze the problem of aggregation of individual fuzzy preferences in a society into a global one that represents the whole society and accomplishes a shortlist of common-sense properties in the spirit of the Arrovian model for crisp preferences. We introduce a new technique that allows us to control a fuzzy preference by means of five crisp binary relations. This leads to an Arrovian impossibility theorem in this particular fuzzy setting.

Strategic Insights into the Cauvery River Dispute in India

For hundreds of years, conflicts in water sharing have existed all around the globe. Cauvery River, in the southern part of India, has been in the midst of such conflict for the last 130 years. Historically, the conflict has been about the right to use water and the states/provinces in conflict have used the water from the river for agricultural purposes. Due to industrialization in the late 1980s and increasing population, water availability in the region has become stressed. Climate change has exacerbated the region’s water availability issues. Faltering rainfall has caused unrest in the region, and the traditional methods of water sharing are dwindling under political pressure. Without a climate change strategy, the governments of these states will never be able to solve this complex issue at hand. The Graph Model for Conflict Resolution (GMCR) is applied to understand the nuances of this conflict. It models the preferences of the decision-makers (the states of Tamil Nadu and Karnataka) and the common option (goal) they can reach to potentially solve the conflict. Fuzzy preferences along with option prioritization is also applied to this conflict in order to account for the uncertainties in the decision-makers’ preferences. The purpose of this paper is to nudge decision-makers in a productive direction to overcome the long-impending political standoff, while introducing a new methodology of looking into this old conflict.