Constrained real-parameter optimization with generalized differential evolution

被引：80
|
作者：
Kukkonen, Saku [1 ]
Lampinen, Jouni [1 ]
机构：
[1] Lappeenranta Univ Technol, Dept Informat Technol, POB 20, FIN-53851 Lappeenranta, Finland
来源：
2006 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-6 | 2006年
关键词：
D O I：
10.1109/CEC.2006.1688310
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents results for the CEC 2006 Special Session on Constrained Real-Parameter Optimization where the Generalized Differential Evolution (GDE) has been used to solve given test problems. The given problems consist of 24 problems having one objective function and one or more in-/equality constraints. Almost all the problems were solvable in a given maximum number of solution candidate evaluations. The paper also shows how GDE actually needs lower number of function evaluations than usually required.
引用
收藏
页码：207 / +
页数：2
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