| Article ID: | iaor19991479 |
| Country: | United Kingdom |
| Volume: | 36 |
| Issue: | 7 |
| Start Page Number: | 79 |
| End Page Number: | 89 |
| Publication Date: | Oct 1998 |
| Journal: | Computers & Mathematics with Applications |
| Authors: | Liu Baoding |
| Keywords: | multi-level programming, genetic algorithms, Nash theory and methods, minimax problem |
Multilevel programming offers a means of studying decentralized noncooperative decision systems. Unfortunately, multilevel programming is lacking efficient algorithms due to its computational difficulties such as nonconvexity and NP-hardness. This paper will design a genetic algorithm for solving Stackelberg–Nash equilibrium of nonlinear multilevel programming with multiple followers in which there might be information exchange among the followers. As a byproduct, we obtain a means for solving classical minimax problems. Finally, some numerical examples are provided to illustrate the effectiveness of the proposed genetic algorithm.