A genetic algorithm approach for set covering problems

Author

Huang, Wen-Chih ; Kao, Cheng-Yan ; Horng, Jorng-Tzong

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan

fYear

1994

fDate

27-29 Jun 1994

Firstpage

569

Abstract

We introduce a genetic algorithm approach for set covering problems. Since the set covering problems are constrained optimization problems we utilize a new penalty function to handle the constraints. In addition, we propose a mutation operator which can approach the optima from both sides of feasible/infeasible borders. We experiment with our genetic algorithm to solve several instances of computationally difficult set covering problems that arise from computing the 1-width of the incidence matrix of Steiner triple systems. We have found better solutions than the currently best-known solutions for two large test problems

Keywords

constraint handling; genetic algorithms; optimisation; Steiner triple systems; constrained optimization problems; genetic algorithm approach; incidence matrix; mutation operator; penalty function; set covering problems; Computational efficiency; Computer science; Constraint optimization; Genetic algorithms; Legged locomotion; Linear programming; Processor scheduling; Resource management; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1899-4

Type

conf

DOI

10.1109/ICEC.1994.349997

Filename

349997