Genetic algorithm approach for set covering problems

Wen Chih Huang, Cheng Yan Kao, Jorng Tzong Horng

Research output: Contribution to conferencePaperpeer-review

18 Scopus citations

Abstract

In this paper, 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.

Original languageEnglish
Pages569-574
Number of pages6
StatePublished - 1994
EventProceedings of the 1st IEEE Conference on Evolutionary Computation. Part 1 (of 2) - Orlando, FL, USA
Duration: 27 Jun 199429 Jun 1994

Conference

ConferenceProceedings of the 1st IEEE Conference on Evolutionary Computation. Part 1 (of 2)
CityOrlando, FL, USA
Period27/06/9429/06/94

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