A Gene-Level Hybrid Crossover Operator for Multiobjective Evolutionary Algorithm
ISCMI '15 Proceedings of the 2015 Second International Conference on Soft Computing and Machine Intelligence (ISCMI)(2015)
Abstract
This study proposes a novel recombination operator, called hybrid crossover operator (HX), which is performed in gene level of chromosome to enhance the optimization performance of multi-objective evolutionary algorithms (MOEAs). The proposed HX operator combines the advantages of simulated binary crossover with local search ability and differential evolution with strong global search capability. When HX is embedded into two state-of-the-art MOEAs, i.e., NSGA-II and MOEA/D-DE, the experimental results validate the improvement of HX when compared to the original counterpart.
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Key words
DIFFERENTIAL EVOLUTION,OPTIMIZATION
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