Embedding multi-attribute decision making into evolutionary optimization to solve the many-objective combinatorial optimization problems

Evolutionary Multi-objective optimization is a popular tool to generate a set of finite optimal alternatives, usually called a Pareto-optimal set, for decision making of engineering optimization problems. However, the current evolutionary algorithms using Pareto optimality or modified Pareto optimal...

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Bibliographic Details
Published in:Journal of Grey System Vol. 28; no. 3; p. 124
Main Authors: Zhang, Yicha, Wang, Weijun, Bernard, Alain
Format: Journal Article
Language:English
Published: Burnham Research Information Ltd 01.01.2016
Subjects:
Combinatorial optimization
Evolutionary algorithms
Methods
Multiple criteria decision making
United States
ISSN:0957-3720, 2396-9040
Online Access:Get full text
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Summary:Evolutionary Multi-objective optimization is a popular tool to generate a set of finite optimal alternatives, usually called a Pareto-optimal set, for decision making of engineering optimization problems. However, the current evolutionary algorithms using Pareto optimality or modified Pareto optimality as a ranking metric suffer from the decrease of selection pressure and further deterioration of search capability as the number of objectives increases. To tackle these difficulties when facing the Many-objective optimization problems (number of objectives > 4), this paper introduces a method which embeds an integrated Multi-Attribute Decision Making (MADM) model into the evolutionary optimization as a non-Pareto ranking for selection. This method can convert the Many-objective optimization problems into Single-objective optimization problems, which can greatly reduce the computational complexity by limiting the search to the region of user preference and also diminish the decision making difficulty by providing a user-preferred single optimal solution on or near the Pareto-optimal front. The classical Multi-objective traveling salesman problem (MOTSP), which is a template of many discrete combinatorial optimization problems, is selected as illustrative numerical example for verification and demonstration. Keywords: Many-objective Optimization; Multi-attribute Decision Making; Grey Theory; Evolutionary Algorithm
Bibliography:SourceType-Scholarly Journals-1
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ISSN:0957-3720
2396-9040