2008•Computer Engineering and Applications JournalRequires access

Improved multi-objective evolutionary algorithm based on differential evolution

Jinhua Zheng

Abstract

Recently,the use of evolutionary algorithms(EAs) to solve the Multi-objective Optimization Problems(MOPs) has attracted much attention.EA is a population based optimized approach which can find a group of Pareto-optimal solutions in a single run.Differential Evolution(DE) is a branch of EA that is developed to handle problems over continuous domains.An improved Multi-objective Evolutionary Algorithm is proposed based on Differential Evolution(CDE) to solve MOPs.The proposed algorithm is compared to the other two classical Multi-objective Evolutionary algorithms(MOEAs) NSGA-Ⅱ and SPEA2 with the experiment results.

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Key concepts: Evolutionary algorithm, Differential evolution, Mathematical optimization, Computer science, Evolutionary computation, Multi-objective optimization, Pareto principle, Population