Abstract:

The biogeography-based optimization algorithm(BBO) is a new intelligent algorithm. It receives wide academic attention and research, and showed a broad application in many fields. In order to improve the performance of the algorithm, an improved BBO algorithm is proposed, which is based on the combination of the local search strategy in differential evolution(DE) algorithm and the migration strategy in BBO algorithm. The improvement of the migration operator and mutation operator make the evolution and the optimization of the algorithm much better. Meanwhile, the research attempts to apply the improved biogeography optimization algorithm to the cylindricity error evaluation. The process of optimization combines the minimum zone method, according to the national standard, to achieve the purpose of the optimization of the cylindricity error mathematical model of objective function. The results gotten from experiments on the objective function optimization and the results from other methods are compared, which verifies the feasibility of the method and the correctness and superiority.

Key words: cylindricity error evaluation, differential evolution, minimum zone method, biogeography-based optimization algorithm