Article | Nordic MPS 2004. The Ninth Meeting of the Nordic Section of the Mathematical Programming Society | Optimization and Evolutionary Search: Related Issues

Title:
Optimization and Evolutionary Search: Related Issues
Author:
Maumita Bhattacharya: Charles Sturt University, Australia
Download:
Full text (pdf)
Year:
2004
Conference:
Nordic MPS 2004. The Ninth Meeting of the Nordic Section of the Mathematical Programming Society
Issue:
014
Article no.:
007
No. of pages:
1
Publication type:
Abstract
Published:
2004-12-28
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press; Linköpings universitet


Evolutionary algorithms (EA) have been long accepted as efficient global optimizers. Given a search space S and an objective function g defined on it; the problem is to find the global maximum (or minimum) of g in S. To apply EA’s heuristic search; the coding function or representation ? is created; that partially maps S to the finite chromosome space C. The genetic operators are used to create new solutions such that Cn ? Cm.

However; as the evolutionary search progresses; it is important to avoid reaching a state where the genetic operators can no longer produce superior offspring; prematurely. This is likely to occur when the search space reaches a homogeneous or near-homogeneous configuration converging to a local optimal solution. Maintaining a certain degree of population diversity is widely believed to help curb this problem. This paper discusses the problem of premature convergence related to EA based optimization. A novel technique is presented; that uses informed genetic operations to reach promising; but un/under-explored areas of the search space; while discouraging local convergence; to curb premature convergence. Elitism is used at a different level aiming at convergence. The proposed technique’s improved performance in terms solution precision and convergence characteristics is observed on a number of benchmark test functions with a genetic algorithm (GA) implementation.

Nordic MPS 2004. The Ninth Meeting of the Nordic Section of the Mathematical Programming Society

Author:
Maumita Bhattacharya
Title:
Optimization and Evolutionary Search: Related Issues
References:
No references available

Nordic MPS 2004. The Ninth Meeting of the Nordic Section of the Mathematical Programming Society

Author:
Maumita Bhattacharya
Title:
Optimization and Evolutionary Search: Related Issues
Note: the following are taken directly from CrossRef
Citations:
No citations available at the moment