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Research and Application on Multi-Objective Group Decision-Making Based on Linguistic Preference Relations

Author: QinLi
Tutor: PeiZuo
School: West China University
Course: Computer Software and Theory
Keywords: Multi-objective group decision - making Pareto optimal solution IULOWA operator NSGA-Ⅱ algorithm
CLC: TP18
Type: Master's thesis
Year: 2009
Downloads: 69
Quote: 1
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Abstract


The multi-objective decision-making process of many possible options to achieve a variety of purposes or goals. In real life, we often encounter the need for multi-objective decision-making problems, its core idea is to find a satisfactory solution, but not optimal solution. This is because in the complex decision-making environment, the target is often conflicting and incommensurability of leading to the optimal solution does not exist. Multi-objective decision model based on preference relations are few and far between, and group decision-making related to the model is very small. Make major decisions when a person's intelligence is not enough. Therefore, in this paper, we explore a multi-objective group decision-making model based on the relationship between language preferences. The model has the following four characteristics: 1, based on the language preference relations. In making decisions, it is difficult to precise numerical description preferences. To this end, we introduce the language preference relations, decision-makers on the program will be a very natural way to express preferences. 2, based on the Pareto optimal solutions Pareto optimal solution concept is in line with the multi-objective problem's own characteristics, so, in the optimization of the algorithm of choice, we use the algorithm with Pareto thought. The algorithm more popular non-inferiority improved hierarchical genetic algorithm NSGA-II. With this algorithm, can be evenly distributed and spread better approximation of the Pareto optimal solution set. 3, based on the target satisfaction we introduce the concept of goal satisfaction to the large number of Pareto optimal solution set reduced to only satisfied with the decision makers of the solution set, so as to reduce the burden of decision-making is. Based on group decision-making because people decisions more in line with realistic needs, so our model in group decision-making based on the proposed. Use aggregation operator can very easily polymerized view of the decision makers. In the model, we have adopted the language preferences IULOWA operator to aggregate decision makers. In addition, we use NSGA-Ⅱ algorithm to solve discrete problems to expand the scope of its application to improve its practical value. We also developed a new role for induction variables, so that it not only has the task of sort and calculate W weight, and also use it to calculate linguistic distance, process links the OWA pair. In order to alleviate the burden of decision-making, to improve the speed of decision-making, we also studied some of the properties of the model and give a proof. In the last article, we apply the model to solve the complex parts Collaborative Manufacturing optimal allocation of resources, and get a good result.

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