摘要
柔性作业车间调度问题允许一道工序可以在多个可选机器上进行加工,减少了机器约束,增加了求解难度,是典型的NP难问题。结合其特点,设计了一种精英进化策略遗传算法求解柔性作业车间调度问题。提出了解阈值的指标,使得外部精英库中不仅保留算法每次迭代过程中的最优解,而且保留最优值相等而调度方案不同的解,为调度人员提供更多选择。通过制造企业中的实际案例和其他文献中的案例对提出的精英进化策略遗传算法进行测试,结果证明了提出方法的有效性。
The flexible Job-Shop scheduling problem is a typical NP-hard problem, which allows an operation can be processed in multiple alternative machines, reducing the machine constraints and increasing the difficulty of solving the problem. Combined with its characteristics, this paper designed an improved genetic algorithm with elite evolution strategy to solve the flexible Job-Shop scheduling problem. It proposed the solution threshold index to identify the good solutions. The elite library not only could save the optimal solution in the each iteration process, but also could save the different scheduling scheme with the same objective values to provide more options for scheduling workers. The actual cases from the aeronautical enterprises and other cases in the literature were tested through the proposed algorithm. The results prove the effectiveness of the proposed method.
作者
张国辉
张凌杰
吴立辉
张海军
Zhang Guohui Zhang Lingjie Wu Lihui Zhang Haijun(School of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou 450015, China Dept. of Mechanical Electronic ＆ Information Engineering, Henan Vocational College of Water Conservancy ＆ Environment, Zhengzhou 450008, China School of Mechanical ＆ Electrionic Engineering, Henan University of Technology, Zhengzhou 450052, China)
出处
《计算机应用研究》
CSCD
北大核心
2016年第12期3579-3581,3666,共4页
Application Research of Computers
基金
国家自然科学基金资助项目(61203179
71201048)
航空科学基金资助项目(2014ZG55016)
河南省高校科技创新人才支持计划资助项目(14HASTIT006)
河南省高等学校重点科研资助项目(16A460025)
关键词
精英进化策略
柔性作业车间调度
遗传算法
解阈值
elite evolution strategy
flexible Job-Shop scheduling
genetic algorithm
solution threshold
