A Generalized Differential Evolution Combined with EDA for Multi-objective Optimization Problems

Authors:
Wang Chen;Yan-Jun Shi;Hong-Fei Teng
Affiliations:
School of Mechanical Engineering, Dalian University of Technology, Dalian, P.R. China 116024;School of Mechanical Engineering, Dalian University of Technology, Dalian, P.R. China 116024;School of Mechanical Engineering, Dalian University of Technology, Dalian, P.R. China 116024
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Year:
2008

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Abstract

This paper proposed a multi-objective evolutionary algorithm (called by GDE-EDA hereinafter). The proposed algorithm combined a generalized differential evolution (DE) with an estimation of distribution algorithm (EDA). This combination can simultaneously use global information of population extracted by EDA and differential information by DE. Thus, GDE-EDA can obtain a better distribution of the solutions by EDA while keeping the fast convergence exhibited by DE. The experimental results of the proposed GDE-EDA algorithm were reported on a suit of widely used test functions, and compared with GDE and NSGA-II in the literature.