DocumentCode
2558233
Title
An improved species conserving genetic algorithm for multimodal optimization
Author
Dingcai Shen ; Xia, Xuewen
Author_Institution
Sch. of Comput. & Inf. Sci., Hubei Eng. Univ., Xiaogan, China
fYear
2012
fDate
29-31 May 2012
Firstpage
1156
Lastpage
1160
Abstract
A new method for finding multiple solutions of multimodal optimization problems is proposed in this paper. To avoid the necessity of specifying a niche radius, the proposed method adopts hybrid of species conservation and hill-valley detection mechanism. The proposed method is compared with classical Species Conservation Genetic Algorithm (SCGA) on a number of standard benchmark problems. The experimental results show that the new approach performs better in finding all optima with no additional parameters introduced.
Keywords
genetic algorithms; SCGA; hill-valley detection mechanism; multimodal optimization; niche radius; species conservation genetic algorithm; Algorithm design and analysis; Educational institutions; Evolutionary computation; Genetic algorithms; Optimization; Radio frequency; Standards; Genetic Algorithm; Hill-valley Detecting; Multimodal Optimization; Species Conservation;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location
Chongqing
ISSN
2157-9555
Print_ISBN
978-1-4577-2130-4
Type
conf
DOI
10.1109/ICNC.2012.6234613
Filename
6234613
Link To Document