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An enhanced multi-objective evolutionary optimization algorithm with inverse model. (English) Zbl 1459.90229
Summary: Multi-objective evolutionary algorithm based on the inverse model (IM-MOEA) is a popular method to solve multi-objective optimization problems (MOPs). However, IM-MOEA has some drawbacks such as low accuracy and difficulty in dealing with MOPs with irregular PFs. To address these issues, adaptive reference vector mechanism and nonrandom grouping strategy are employed in IM-MOEA, which enhances the reliability of the inverse model. In addition, a modified selection mechanism is used to choose candidate solutions. Further, an enhanced IM-MOEA with adaptive reference vectors and nonrandom grouping (AN-IMMOEA) is proposed in this paper. The experimental results on 27 MOPs indicate that the proposed method has a better performance than other MOEAs.
MSC:
90C59 Approximation methods and heuristics in mathematical programming
68W50 Evolutionary algorithms, genetic algorithms (computational aspects)
90C29 Multi-objective and goal programming
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