Using hybrid metaheuristic approaches to solve bi-level linear programming problem for supply chain management

Bi-level linear programming is a technique for modeling decentralized decision. It consists of the upper level and lower level objectives. Thus, this paper intends to apply bi-level linear programming to supply chain management and develops an efficient method based on hybrid of genetic algorithm and particle swarm optimization. The performance of the proposed method is ascertained by comparing the results with other metaheuristic approaches.