Two‐level 0‐1 Programming through Genetic Algorithms with Sharing Scheme Using Cluster Analysis Methods

This paper deals with the two level 0–1 programming problems in which there are two decision makers (DMs); the decision maker at the upper level and the decision maker at the lower level. The authors modify the problematic aspects of a computation method for the Stackelberg solution which they previously presented, and thus propose an improved computation method. Specifically, a genetic algorithm (GA) is proposed with the objective of boosting the accuracy of solutions while maintaining the diversity of the population, which adopts a clustering method instead of calculating distances during sharing. Also, in order to eliminate unnecessary computation, an additional algorithm is included for avoiding obtaining the rational reaction of the lower level DM in response to upper level DM’s decisions when necessary. In order to verify the effectiveness of the proposed method, it is intended to make a comparison with existing methods by performing numerical experiments into both the accuracy of solutions and the ...