Two-Decision-Maker Conflict Resolution with Fuzzy Preferences

2014 ◽  
Vol 2 (2) ◽  
pp. 40-59
Author(s):  
Mubarak S. Al-Mutairi
Keyword(s):  
Fuzzy Logic ◽  
Conflict Resolution ◽  
Decision Maker ◽  
Decision Makers ◽  
Fuzzy Approach ◽  
Model Uncertainties ◽  
Preference Information ◽  
Fuzzy Preferences ◽  
Illustrative Application ◽  
Fuzzy Preference

A unique fuzzy approach is developed to model uncertainties in the preferences of a decision maker involved in a conflict. Human judgments, including expressing preferences over a set of feasible outcomes or states in a conflict, are usually imprecise. Situations characterized by vagueness, impreciseness, incompleteness and ambiguity, are often reflected in the decision maker's preferences. When modeling a conflict, it is assumed that the decision makers, the courses of actions available for each, and the preferences of each decision maker are known. When the preferences of the decision maker over a certain set of actions are not known with certainty, this could affect the overall equilibria which are predicted in an analysis. Hence, fuzzy logic is used to handle imprecise or vague preference information so that realistic equilibria can be found. The well-known game of Prisoner's Dilemma, in which one must decide whether or not to cooperate, is employed as an illustrative application to demonstrate how the fuzzy preference methodology works in practice.

scholarly journals Comparing interactive evolutionary multiobjective optimization methods with an artificial decision maker

2021 ◽  
Author(s):  
Bekir Afsar ◽  
Ana B. Ruiz ◽  
Kaisa Miettinen
Keyword(s):  
Multiobjective Optimization ◽  
Decision Maker ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Decision Makers ◽  
Interactive Methods ◽  
Preference Information ◽  
Evolutionary Methods ◽  
Solution Processes ◽  
Trade Offs

AbstractSolving multiobjective optimization problems with interactive methods enables a decision maker with domain expertise to direct the search for the most preferred trade-offs with preference information and learn about the problem. There are different interactive methods, and it is important to compare them and find the best-suited one for solving the problem in question. Comparisons with real decision makers are expensive, and artificial decision makers (ADMs) have been proposed to simulate humans in basic testing before involving real decision makers. Existing ADMs only consider one type of preference information. In this paper, we propose ADM-II, which is tailored to assess several interactive evolutionary methods and is able to handle different types of preference information. We consider two phases of interactive solution processes, i.e., learning and decision phases separately, so that the proposed ADM-II generates preference information in different ways in each of them to reflect the nature of the phases. We demonstrate how ADM-II can be applied with different methods and problems. We also propose an indicator to assess and compare the performance of interactive evolutionary methods.

Material Selection Using a Novel Multiple Attribute Decision Making Method

2012 ◽  
pp. 252-266
Author(s):  
R. V. Rao ◽  
B. K. Patel
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Maker ◽  
Design Process ◽  
Material Selection ◽  
Multiple Attribute Decision Making ◽  
Decision Makers ◽  
Selection Problem ◽  
Multiple Attribute ◽  
Selection Of

Selection of a most appropriate material is a very important task in design process of every product. There is a need for simple, systematic, and logical methods or mathematical tools to guide decision makers in considering a number of selection attributes and their interrelations and in making right decisions. This paper proposes a novel multiple attribute decision making (MADM) method for solving the material selection problem. The method considers the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the integrated weights of importance of the attributes. Furthermore, the method uses fuzzy logic to convert the qualitative attributes into the quantitative attributes. Two examples are presented to illustrate the potential of the proposed method.

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

2020 ◽  
Vol 39 (5) ◽  
pp. 6721-6731
Author(s):  
Nannan Wu ◽  
Yejun Xu ◽  
Lizhong Xu ◽  
Huimin Wang
Keyword(s):  
Sustainable Development ◽  
Conflict Resolution ◽  
Preference Relation ◽  
Graph Model ◽  
Decision Makers ◽  
The Novel ◽  
Equilibrium Solutions ◽  
Fuzzy Preferences ◽  
Fuzzy Solution ◽  
Behavior Characteristics

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.

scholarly journals The Scheduling Decision of a Refinery: The Decision Maker in Search of Conflict Resolution

2015 ◽  
Vol 3 (1) ◽  
pp. 36
Author(s):  
Thais Spiegel ◽  
Heitor Mansur Caulliraux
Keyword(s):  
Decision Making ◽  
Conflict Resolution ◽  
Decision Maker ◽  
Comprehensive Evaluation ◽  
Refining Process ◽  
Decision Makers ◽  
Hierarchical Decision ◽  
The Face ◽  
Decision Making Processes ◽  
Oil Company

Refineries typically gather a set of activities that are complex and dynamic. Adding to the complexity of the refining process, there is also great freedom in refinery operations, multiple possible arrangements to convert certain oils in derivatives. In this context, this paper focuses on the decision-making processes that lead refiners of an integrated oil company in their day to day. As decision making, the text refers to a process that always brings a kind of conflict resolution, in which conflicting goals have to be negotiated and reconciled. The object of analysis is inserted in hierarchical decision-making processes, e.g. a breakdown process, which begins with a comprehensive evaluation and then divides the decision into ever smaller and more defined elements so that they are interdependent. The output at an aggregated level is then input in the next detailed level. In each of the hierarchical levels, the decision-making is the result of a problem presented in a certain context to a decision maker. This decision maker will be responsible for the direction of the refinery production in which he/she is allocated. The programmer of each refinery have general guidelines that should be considered, albeit non-explicitly or non-definable way, these take the form of criteria in some cases of technical origin and in other situations derived from the business. Given these aspects, this article presents a critical and analytical view in the face of dilemmas that emerge before the search of the decision makers to converge scheduling production considering both set of criteria.

scholarly journals Water allocation analysis of the Zhanghe River basin using the Graph Model for Conflict Resolution with incomplete fuzzy preferences

2019 ◽  
Vol 11 (4) ◽  
pp. 1099 ◽  
Author(s):  
Nannan Wu ◽  
Yejun Xu ◽  
D. Kilgour
Keyword(s):  
Conflict Resolution ◽  
River Basin ◽  
Water Allocation ◽  
Common Property ◽  
Preference Relation ◽  
Real Life ◽  
Graph Model ◽  
Additive Consistency ◽  
Fuzzy Preferences ◽  
Fuzzy Preference

An incomplete fuzzy preference framework for the Graph Model for Conflict Resolution (GMCR) is proposed to handle both complete and incomplete fuzzy preference information. Usually, decision makers’ (DMs’) fuzzy preferences are assumed to be complete fuzzy preference relations (FPRs). However, in real-life situations, due to lack of information or limited expertise in the problem domain, any DM’s preference may be an incomplete fuzzy preference relation (IFPR). An inherent advantage of the proposed framework for GMCR is that it can complete the IFPRs based on additive consistency, which is a special form of transitivity, a common property of preferences. After introducing the concepts of FPR, IFPR, and transitivity, we propose an algorithm to supplement IFPR, that is, to find an FPR that is a good approximation. To illustrate the usefulness of the incomplete fuzzy preference framework for GMCR, we demonstrate it using to a real-world conflict over water allocation that took place in the Zhanghe River basin of China.

Research on the optimal aggregation method of fuzzy preference information based on spatial Steiner-Weber point

2021 ◽  
pp. 1-19
Author(s):  
Wei Liu ◽  
Yuhong Wang
Keyword(s):  
Three Dimensional ◽  
Spatial Aggregation ◽  
Decision Makers ◽  
Aggregation Method ◽  
Group Preference ◽  
Preference Information ◽  
Novel Method ◽  
Three Dimensional Coordinate ◽  
Plant Growth Simulation Algorithm ◽  
Fuzzy Preference

In view of the present situation that most aggregation methods of fuzzy preference information are extended or mixed by classical aggregation operators, which leads to the aggregation accuracy is not high. The purpose of this paper is to develop a novel method for spatial aggregation of fuzzy preference information. Thus we map the fuzzy preference information to a set of three-dimensional coordinate and construct the spatial aggregation model based on Steiner-Weber point. Then, the plant growth simulation algorithm (PGSA) algorithm is used to find the spatial aggregation point. According to the comparison and analysis of the numerical example, the aggregation matrix established by our method is closer to the group preference matrices. Therefore, the optimal aggregation point obtained by using the optimal aggregation method based on spatial Steiner-Weber point can best represent the comprehensive opinion of the decision makers.

Some Algorithms for Group Decision Making with Intuitionistic Fuzzy Preference Information

2014 ◽  
Vol 22 (04) ◽  
pp. 505-529 ◽  
Author(s):  
Huchang Liao ◽  
Zeshui Xu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Relation ◽  
Decision Makers ◽  
Fuzzy Preference Relation ◽  
Preference Information ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Preference Relation ◽  
Fuzzy Preference

Intuitionistic fuzzy preference relation has turned out to be a powerful structure in representing the decision makers' preference information especially when the decision makers are not able to express their preferences accurately due to the unquantifiable information, incomplete information, unobtainable information, partial ignorance, and so forth. The aim of this paper is to develop some techniques for group decision making with intuitionistic fuzzy preference information. Based on the multiplicative consistency of intuitionistic fuzzy preference relation, three algorithms are proposed for intuitionistic fuzzy group decision making. In the case that the decision makers act as separate individuals, the priority vector of each decision maker can be derived directly from the individual intuitionistic fuzzy preference relation, after which an overall priority vector is obtained by synthesizing those individual priorities together. As for the scenario that the decision makers act as one individual, two different algorithms based on the multiplicative consistency are proposed to deal with this case. The main idea of the former procedure is firstly constructing a social intuitionistic fuzzy preference relation, while that of the later is building a fractional programming model. Some practical examples are given to demonstrate the developed algorithms.

Material Selection Using a Novel Multiple Attribute Decision Making Method

2011 ◽  
Vol 1 (1) ◽  
pp. 43-56 ◽  
Author(s):  
R. V. Rao ◽  
B. K. Patel
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Maker ◽  
Design Process ◽  
Material Selection ◽  
Multiple Attribute Decision Making ◽  
Decision Makers ◽  
Selection Problem ◽  
Multiple Attribute ◽  
Selection Of

Selection of a most appropriate material is a very important task in design process of every product. There is a need for simple, systematic, and logical methods or mathematical tools to guide decision makers in considering a number of selection attributes and their interrelations and in making right decisions. This paper proposes a novel multiple attribute decision making (MADM) method for solving the material selection problem. The method considers the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the integrated weights of importance of the attributes. Furthermore, the method uses fuzzy logic to convert the qualitative attributes into the quantitative attributes. Two examples are presented to illustrate the potential of the proposed method.

Decision making based on intuitionistic fuzzy preference relations with additive approximate consistency

2020 ◽  
Vol 39 (3) ◽  
pp. 4041-4058
Author(s):  
Fang Liu ◽  
Xu Tan ◽  
Hui Yang ◽  
Hui Zhao
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Real Interval ◽  
Preference Relations ◽  
Intuitionistic Fuzzy ◽  
Proposed Model ◽  
Fuzzy Preference Relations ◽  
Novel Concept ◽  
Fuzzy Weights ◽  
Fuzzy Preference

Intuitionistic fuzzy preference relations (IFPRs) have the natural ability to reflect the positive, the negative and the non-determinative judgements of decision makers. A decision making model is proposed by considering the inherent property of IFPRs in this study, where the main novelty comes with the introduction of the concept of additive approximate consistency. First, the consistency definitions of IFPRs are reviewed and the underlying ideas are analyzed. Second, by considering the allocation of the non-determinacy degree of decision makers’ opinions, the novel concept of approximate consistency for IFPRs is proposed. Then the additive approximate consistency of IFPRs is defined and the properties are studied. Third, the priorities of alternatives are derived from IFPRs with additive approximate consistency by considering the effects of the permutations of alternatives and the allocation of the non-determinacy degree. The rankings of alternatives based on real, interval and intuitionistic fuzzy weights are investigated, respectively. Finally, some comparisons are reported by carrying out numerical examples to show the novelty and advantage of the proposed model. It is found that the proposed model can offer various decision schemes due to the allocation of the non-determinacy degree of IFPRs.

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