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.
|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||Proceedings of the 1st IEEE Conference on Evolutionary Computation. Part 1 (of 2)|
|City||Orlando, FL, USA|
|Period||27/06/94 → 29/06/94|