An asymmetric multileveled symbiotic evolutionary algorithm for integrated FMS scheduling

This paper considers the integrated FMS (flexible manufacturing system) scheduling problem (IFSP) consisting of loading, routing, and sequencing subproblems that are interrelated to each other. In scheduling FMS, the decisions for the subproblems should be appropriately made to improve resource utilization. It is also important to fully exploit the potential of the inherent flexibility of FMS. In this paper, a symbiotic evolutionary algorithm, named asymmetric multileveled symbiotic evolutionary algorithm (AMSEA), is proposed to solve the IFSP. AMSEA imitates the natural process of symbiotic evolution and endosymbiotic evolution. Genetic representations and operators suitable for the subproblems are proposed. A neighborhood-based coevolutionary strategy is employed to maintain the population diversity. AMSEA has the strength to simultaneously solve subproblems for loading, routing, and sequencing and to easily handle a variety of FMS flexibilities. The extensive experiments are carried out to verify the performance of AMSEA, and the results are reported.