Migrating Birds Optimization Algorithm Used Variable Neighborhood Search for Flexible Job Shop Scheduling

By analyzing the production features of the flexible job shop, a migrating birds optimization algorithm used variable neighborhood search(VNS_MBOA) was proposed by combining the migrating birds optimization and the variable neighborhood search algorithm to solve the production scheduling problem. A segment-based encoding approach is adopted, and a two-phase initialization of the population in the algorithm is performed to improve the quality of the initial solution. On the basis of the characteristics of the problem, two neighborhood structures are designed, based on which a variable neighborhood search algorithm is introduced to enhance the searching capability of VNS_MBOA effectively. Benchmark instances are adopted to test the proposed algorithm, and the simulation results are compared with other algorithms in literature. The computational data demonstrate that the proposed algorithm has certain degree effect for solving the flexible job shop scheduling problem.