摘要
针对柔性作业车间的特点,以最小化完工时间、总机器负荷最小和临界机器负荷最小为目标,提出了基于三方博弈的改进遗传算法求解多目标柔性作业车间调度模型。通过三方博弈,使三个优化目标之间的博弈策略实现最优组合,从而获得子博弈完美纳什均衡,即为问题的优化组合解。为优化种群质量,将改进遗传算法应用于多目标柔性作业车间调度问题的求解过程,采用帕累托分类思想,对种群进行选择和精英保留,以优化种群结构;通过设计交叉、变异和局部搜索机制进一步寻找目标函数的最优解。为证明算法的有效性,运用基准算例对算法的求解性能进行了验证。其结果表明,所提算法在求解结果上有明显的改善,求解效率更高。
Aiming at the characteristics of flexible job shop,the multi-objective flexible job shop scheduling problem with makespan time,total workload of machines and critical machine workload was established.An improved genetic algorithm based on game theory was proposed.In order to obtain the optimal solution,a sub-game perfect Nash equilibrium solution was designed.To optimize the population quality,the improved hybrid genetic algorithm was applied to the multi-objective flexible job shop scheduling problem solving process.The Pareto classification idea was used to optimize the population structure.The optimal solution of the objective function was further searched by crossover,mutation and local search mechanism.Then the benchmark study was used to verify the performance of the algorithm.The results show that the proposed algorithm has generated obvious improvement in the solution result and the solution efficiency is higher.
作者
裴小兵
李依臻
PEI Xiaobing;LI Yizhen(School of Management,Tianjin University of Technology,Tianjin 300384,China)
出处
《工业工程与管理》
CSSCI
北大核心
2020年第4期59-68,94,共11页
Industrial Engineering and Management
基金
国家创新方法工作专项项目(2017IM060200)。
关键词
柔性作业车间
博弈论
纳什均衡
遗传算法
flexible job-shop
game theory
Nash equilibrium
genetic algorithm
