Abstract How to evaluate solutions effectively is a key to solving many-objective optimization problem. An inverted generation distance(IGD+S) indicator is proposed based on IGD indicator, incorporating weak dominance of IGD+ indicator and employing the concept of non-contributing individuals. Convergence and diversity of solution set are evaluated comprehensively. IGD+S indicator is embedded in the framework of evolutionary algorithms, and a multi-objective evolutionary algorithm based on IGD+S indicator is presented. In the process of environmental selection, excellent solutions are selected according to enhanced IGD+S indicator. Experimental results demonstrate that the proposed algorithm is competitive in DTLZ problems and WFG problems.
Fund:Supported by National Natural Science Foundation of China(No.61866025,61772255,61440049), Open Fund of Key Laboratory of Image Processing and Pattern Recognition of Jiangxi Province(No.ET201604246), Special Postgraduate Innovation Foundation of Jiangxi Province(No.YC2017-S327), Jiangxi Foundation of Superiority Science and Technology Innovation Team Building Program(No.20152BCB24004)
Corresponding Authors:
CHEN Hao, Ph.D., associate professor. His research interests include evolutionary algorithms, image processing and pattern recognition.
About author:: LI Ming, Ph.D., professor. His research interests include image processing, pattern recognition and many-objective optimization problem;DUAN Ruru, master student. Her research interests include many-objective optimization problem;XIE Huihua, master student. Her research interests include image processing and pattern recognition.
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2019, Vol. 32 
