An Improved Biogeography-Based Optimization Algorithm for Flow Shop Scheduling Problem

For flow shop scheduling problem, an improved biogeography-based optimization algorithm (IBBO) is proposed. Firstly, the mathematical model of the problem is established with the objective function of minimizing the maximum completion time. Secondly, the NEH algorithm is used to initialize the population. The cosine migration model is introduced to perform the migration operation. Besides the elite retention strategy is added in the iteration process. And the simulated annealing algorithm is combined to improve the optimization ability of biogeography-based optimization algorithm. Finally, on the basis of Taillard example, the performance of the proposed method is analyzed by using ARPD through experimental simulation. The results show the advantages of the improved biogeography-based optimization.