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Novel PIO Algorithm with Multiple Selection Strategies for Many-Objective Optimization Problems 被引量:3
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作者 Zhihua Cui Lihong Zhao +3 位作者 Youqian Zeng Yeqing Ren Wensheng Zhang Xiao-Zhi Gao 《Complex System Modeling and Simulation》 2021年第4期291-307,共17页
With the increase of problem dimensions,most solutions of existing many-objective optimization algorithms are non-dominant.Therefore,the selection of individuals and the retention of elite individuals are important.Ex... With the increase of problem dimensions,most solutions of existing many-objective optimization algorithms are non-dominant.Therefore,the selection of individuals and the retention of elite individuals are important.Existing algorithms cannot provide sufficient solution precision and guarantee the diversity and convergence of solution sets when solving practical many-objective industrial problems.Thus,this work proposes an improved many-objective pigeon-inspired optimization(ImMAPIO)algorithm with multiple selection strategies to solve many-objective optimization problems.Multiple selection strategies integrating hypervolume,knee point,and vector angles are utilized to increase selection pressure to the true Pareto Front.Thus,the accuracy,convergence,and diversity of solutions are improved.ImMAPIO is applied to the DTLZ and WFG test functions with four to fifteen objectives and compared against NSGA-III,GrEA,MOEA/D,RVEA,and many-objective Pigeon-inspired optimization algorithm.Experimental results indicate the superiority of ImMAPIO on these test functions. 展开更多
关键词 pigeon-inspired optimization algorithm many-objective optimization problem multiple selection strategy elite individual retention
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