一种求解多目标柔性作业车间调度问题的改进元胞遗传算法  

Improved cellular genetic algorithm for solving the multi-objective flexible job shop scheduling problem

作　　者：陆曈曈[1] 陈平[2] 万兴余 

机构地区：[1]三峡大学经济与管理学院,宜昌443002 [2]三峡大学机械与动力学院,宜昌443002

出　　处：《现代制造工程》2016年第11期41-49,共9页Modern Manufacturing Engineering

基　　金：国家自然科学基金项目(51275274,71501110);湖北省自然科学基金项目(2014CFB665)

摘　　要：针对最小化最大完工时间、最大机床负荷及总机床负荷的多目标柔性作业车间调度问题,提出一种带有局部搜索策略的自适应元胞遗传算法。该算法在每完成一次种群迭代后,对种群的平均收敛速度进行计算,确定出合适的选择压。根据种群选择压的大小对种群的拓扑结构进行自适应改变。为了减小邻域搜索空间,结合车间调度问题的特点,借鉴正交设计思想设计了基于正交规则的局部搜索策略。通过4个经典多目标柔性车间调度问题的仿真实验以及与其他算法的比较,说明了该算法的有效性和可行性。In order to minimize the makespan, the maximal workload and the total workload simultaneously in the multi-objective flexible job shop scheduling problems, an adaptive cellular genetic algorithm with local search is proposed. In this algorithm, after each iteration of a population,the average convergence rate of the population is calculated to determine the appropriate selection pressure. Then the population＇ s topology changes adaptively according to the selection pressure. To reduce search space, combined with the features of flexible job shop scheduling problem, referencing orthogonal design ideas, a local search strategy is designed based on orthogonal rules. Finally, four typical simulation results are provided to demonstrate the feasibility and effectiveness of the proposed method.

关 键 词：元胞遗传算法 柔性作业车间调度问题 多目标优化 局部搜索 自适应 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]