A Feature-Based Analysis on the Impact of Set of Constraints for ε-Constrained Differential Evolution

被引：2

作者：

Poursoltan, Shayan ^{[1
]}

Neumann, Frank ^{[1
]}

机构：

[1] Univ Adelaide, Sch Comp Sci, Optimisat & Logist, Adelaide, SA 5005, Australia

来源：

NEURAL INFORMATION PROCESSING, PT III | 2015年 / 9491卷

关键词：

OPTIMIZATION;

D O I：

10.1007/978-3-319-26555-1_39

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Different types of evolutionary algorithms have been developed for constrained continuous optimisation. We carry out a feature-based analysis of evolved constrained continuous optimisation instances to understand the characteristics of constraints that make problems hard for evolutionary algorithm. In our study, we examine how various sets of constraints can influence the behaviour of epsilon-Constrained Differential Evolution. Investigating the evolved instances, we obtain knowledge of what type of constraints and their features make a problem difficult for the examined algorithm.

引用

页码：344 / 355

页数：12

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