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 language | English |
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| Pages | 569-574 |
| Number of pages | 6 |
| State | Published - 1994 |
| Event | Proceedings of the 1st IEEE Conference on Evolutionary Computation. Part 1 (of 2) - Orlando, FL, USA Duration: 27 Jun 1994 → 29 Jun 1994 |
Conference
| Conference | Proceedings of the 1st IEEE Conference on Evolutionary Computation. Part 1 (of 2) |
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| City | Orlando, FL, USA |
| Period | 27/06/94 → 29/06/94 |