High-Dimensional Real-Parameter Optimization using Self-Adaptive Differential Evolution Algorithm with Population Size Reduction

被引：103

作者：

Brest, Janez ^{[1
]}

Zamuda, Ales ^{[1
]}

Boskovic, Borko ^{[1
]}

Maucec, Mirjam Sepesy ^{[1
]}

Zumer, Viljem ^{[1
]}

机构：

[1] Univ Maribor, Fac Elect Engn & Comp Sci, SLO-2000 Maribor, Slovenia

来源：

2008 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-8 | 2008年

关键词：

D O I：

10.1109/CEC.2008.4631067

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we investigate a Self-Adaptive Differential Evolution algorithm (jDEdynNP-F) where F and CR control parameters are self-adapted and a population size reduction method is used. Additionally the proposed jDEdynNP-F algorithm uses a mechanism for sign changing of F control parameter with some probability based on the fitness values of randomly chosen vectors, which are multiplied by the F control parameter (scaling factor) in the mutation operation of DE algorithm. The performance of the jDEdynNP-F algorithm is evaluated on the set of 7 benchmark functions provided for the CEC'2008 special session on high-dimensional real-parameter optimization.

引用

页码：2032 / 2039

页数：8

共 34 条

[1] A self-adaptive differential evolution heuristic for two-stage assembly scheduling problem to minimize maximum lateness with setup times [J].