Annealing a genetic algorithm over constraints

Author

Carlson, Susan E. ; Shonkwiler, R.

Author_Institution

Dept. of Mech. Aerosp. & Nucl. Eng., Virginia Univ., Charlottesville, VA, USA

Volume

4

fYear

1998

fDate

11-14 Oct 1998

Firstpage

3931

Abstract

A class of variable fitness genetic algorithms is studied as a technique for use on constrained optimization problems. Fitness is taken as the product of the objective with an “attenuation” factor which is 1 for feasible solutions but some variable fraction of 1 for infeasible ones. It is shown that this technique leads to algorithms which converge in probability to globally optimal feasible solutions. An application of the technique is made to a problem of engineering interest with excellent results: the ground water treatment problem for unconfined aquifers

Keywords

genetic algorithms; groundwater; probability; simulated annealing; water treatment; constrained optimization problems; fitness; globally optimal feasible solutions; ground water treatment problem; unconfined aquifers; variable fitness genetic algorithms; Aerospace engineering; Annealing; Clustering algorithms; Constraint optimization; Design engineering; Design optimization; Genetic algorithms; Genetic engineering; Mathematics; Temperature;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on

Conference_Location

San Diego, CA

ISSN

1062-922X

Print_ISBN

0-7803-4778-1

Type

conf

DOI

10.1109/ICSMC.1998.726702

Filename

726702