Huang Gang

Work place: State Key Laboratory of Digital Manufacturing Equipment & Technology, HUST; Wuhan, China

E-mail: topsearchgao@hotmail.com

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Biography

Author Articles
An Improved Multi-objective Evolutionary Algorithm with the Hybrid Strategies

By Gao Guibing Huang Gang Zhang Guojun

DOI: https://doi.org/10.5815/ijeme.2011.03.12, Pub. Date: 29 Sep. 2011

An improved multi-objective evolutionary algorithm with the hybrid strategies is presented in this paper for multi-objective optimization problems. The evolution process is divided into initial exploration stage, the middle feedback stage and the accelerating convergence stage by the amount of non-dominated individuals in the population. The hybrid strategies and adaptive population structure are employed to improve the behavior of the algorithm at the different stages. The proposed algorithm is validated by 3 benchmark test problems. Compared with three other famous multi-objective algorithms by two quality indicators, the proposed algorithm achieves competitive results.

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