| Article ID: | iaor19971003 |
| Country: | France |
| Volume: | 28 |
| Issue: | 1 |
| Start Page Number: | 1 |
| End Page Number: | 22 |
| Publication Date: | Jan 1994 |
| Journal: | RAIRO Operations Research |
| Authors: | Anandalingam G., Mathieu R., Pittard L. |
| Keywords: | programming: linear |
This paper reports on the use of a genetic algorithm based technique, GABBA, to solve bi-level linear programming (BLLP) problems. GABBA is used to generate the leader’s decision vector, and the follower’s reaction is obtained from the solution of a linear program. GABBA is different from the usual genetic algorithms because the authors only use mutations, alleles of base-10 numbers, and a survival strategy that is suited to BLLP. Results show that, while it take more cpu time, GABBA gets closer to the global optimum than Bard’s grid search technique for problems of most sizes.