An improved niche genetic algorithm based on simulated annealing: SANGA

Author

Zheng, Huanyang

Author_Institution

Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2011

fDate

21-23 Oct. 2011

Firstpage

1

Lastpage

5

Abstract

A simulated annealing based niche genetic algorithm (SANGA) has been presented to strength the optimization ability of niche genetic algorithm (NGA). The improved idea is to define niche formation using probability condition rather than simply distance condition. Individuals who only have close neighbors are inclined to build up niche; individuals who only have far neighbors are likely to depart from niche. The feasibility and validity of the proposed method is proved by the contrast between current NGA based on penalty, NGA based on fitness sharing, NGA based on deterministic crowding and SANGA in some simulation experiments and applications of 0-1 knapsack problem.

Keywords

genetic algorithms; knapsack problems; simulated annealing; 0-1 knapsack problem; deterministic crowding; distance condition; improved niche genetic algorithm; niche formation; optimization ability; probability condition; simulated annealing; Convergence; Entropy; Evolutionary computation; Genetic algorithms; Genetics; Simulated annealing; 0–1 knapsack problem; adaptive mutation; niche genetic algorithm; simulated annealing based niche;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Problem-Solving (ICCP), 2011 International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4577-0602-8

Electronic_ISBN

978-1-4577-0601-1

Type

conf

DOI

10.1109/ICCPS.2011.6092241

Filename

6092241