Paper Info
Title
Low Dimensional Reproduction Strategy for Real-Coded Evolutionary Algorithms
Abstract
The strategy of low dimensional reproduction (LDR) is proposed for real-coded evolutionary algorithms (REAs) in this paper. It preserves some (randomly chosen) components of the local best vector (elite individual) in the reproduction process and let the traditional reproduction operators act on the rest components. Thus it could help the search points escape from the hyperplane where the parents individuals lies, as well as keep them from getting too much decentralized and search mainly along a series of orthogonal directions (coordinate). The LDR strategy provides a universal idea to improve the performance of REAs. Four REAs are taken as examples to show the effect of the strategy. Numerical results show that the proposed strategy can accelerate the convergence speed of the applied algorithms considerably. In addition, the strategy is computational saving, easy to implement, and easy to control.
Year
DOI
Venue
2008
10.1109/ICIS.2008.37
ACIS-ICIS
Keywords
Field
DocType
computational saving,low dimensional reproduction,evolutionary algorithm,proposed strategy,meta heuristics,evolutionary computation,real-coded evolutionary algorithm,global optimization,applied algorithm,convergence speed,rea,ldr strategy,elite individual,real-coded evolutionary algorithms,traditional reproduction operator,search point,real-coded,low dimensional reproduction strategy,reproduction process,acceleration,particle swarm optimization,genetic algorithms,genetic programming,mathematics,arithmetic,information science
Convergence (routing),Mathematical optimization,Global optimization,Evolutionary algorithm,Computer science,Evolutionary computation,Evolution strategy,Hyperplane,Evolutionary programming,Metaheuristic
Conference
ISBN
Citations 
PageRank 
978-0-7695-3131-1
0
0.34
References 
Authors
9
3
Name
Order
Citations
PageRank
Changtong Luo1365.66
Shao-Liang Zhang29219.06
Bo Yu35311.35