批量无等待调度问题的微粒群蛙跳混合优化算法

摘要

This paper proposed the effective hybrid algorithm of particle swarm optimization ( PSO ) algorithm and shuffled frog- leaping algorithm ( SFLA ) for solving the lot-streaming flow shop scheduling problem with the criterion of minimizing maximum completion time ( i. e. , makespan ) under no-wait production cases. Combining the strong global convergence of particle swarm optimization algorithm and the depth search of the shuffled frog-leaping algorithm, proposed three hybrid algorithms, which could balance local convergence and depth search ability. The computational results and comparisons show that the proposed hybrid algorithms are effective and efficient for random instants in finding better solutions for the problem considered.%将离散微粒群与蛙跳算法相结合解决以最大完工时间为指标的批量无等待流水线调度问题.结合微粒群算法较强的全局收敛能力和蛙跳算法较强的深度搜索能力,设计了三种混合算法,平衡了算法的全局开发能力和局部探索能力.对随机生成不同规模的实例进行了广泛的实验,仿真实验结果的比较表明了所得混合算法的有效性和高效性.