Journal Article10.1016/j.swevo.2023.101272
A two-stage adaptive reference direction guided evolutionary algorithm with modified dominance relation for many-objective optimization
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TL;DR: In this paper , a two-stage adaptive reference point guided evolutionary algorithm with APA-based dominance relation for many-objective optimization problems (named AREA-APA) is proposed.
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Abstract: Traditional dominance-based multi-objective evolutionary algorithms cease to be effective as the number of objectives increases due to the non-dominated sorting mechanism. Accordingly, a novel clustering indicator founded on the penalty-based adaptive rectangular area (APA) between solution and reference direction is proposed to assist in non-dominated levels sorting to deal with this issue. However, directly predefined reference directions with uniform distribution usually cause deteriorated performance in solving multi-objective problems with irregular Pareto fronts. Thus, an adaptive adjustment method guided by the local population is implemented in this paper. At this rate, a two-stage adaptive reference point guided evolutionary algorithm with APA-based dominance relation for many-objective optimization problems (named AREA-APA) is proposed and tested for solving these multi-objective optimization problems (including constrained and unconstrained problems). The proposed algorithm is proven to achieve comparable performance on scalable benchmark problems compared with state-of-the-art algorithms.
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