Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4633854 | Applied Mathematics and Computation | 2009 | 11 Pages |
Abstract
A novel genetic algorithm is described in this paper for the problem of constrained optimization. The algorithm incorporates modified genetic operators that preserve the feasibility of the trial solutions encoded in the chromosomes, the stochastic application of a local search procedure and a stopping rule which is based on asymptotic considerations. The algorithm is tested on a series of well-known test problems and a comparison is made against the algorithms C-SOMGA and DONLP2.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Ioannis G. Tsoulos,