An evolutionary approach to constrained sampling optimization problems

详细信息    查看全文

• 作者：P. Caamañ ; o ^{pcsobrino@udc.es} ; G. Varela ^{gervasio.varela@udc.es} ; R.J. Duro ; ^{richard@udc.es}
• 关键词：Optimization ; Evolutionary algorithms ; Constrained sampling problems ; Constrained sampling evolutionary algorithm
• 刊名：Applied Soft Computing
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：51
• 期：Complete
• 页码：266-279
• 全文大小：2035 K
• 卷排序：51

文摘

Presentation of the general constrained sampling (CS) approach for evolutionary algorithms (EAs). Development of the Constrained Sampling Differential Evolution algorithm (CS-DE). Study of the behavior and performance of CS-DE as compared to the standard DE for different constraint levels and different target selection strategies over different types of fitness landscapes. Analysis of these behaviors in relation to the landscape features, especially in terms of the distribution of attraction basins and their relative sizes.