Abstract:

Aiming at the flexible job shop scheduling problems of limited AGV transportation resources in the intelligent manufacturing environments， an integrated scheduling model for limited AGV transportation resources was established with the objective of minimizing the maximum completion time， total energy consumption and the delivery penalty value of workpieces. An improved NSGA -II solution algorithm was proposed to construct a three-stage coding scheme for the integrated scheduling model， and three initialization rules were designed to improve the quality and diversity of the initial population. Combined with the critical path， an improved variable neighborhood search was proposed to enhance the local search capability of the algorithm. In the experimental part， the algorithm was compared with other algorithms using various evaluation indexes， and the experimental results show that the algorithm may effectively solve the integrated scheduling problems of limited AGV transportation resources under different sizes of standard test cases and actual production cases of aviation enterprises. Meanwhile， the effectiveness of the integrated scheduling model was analyzed under different numbers of AGVs， and it is concluded that the number of AGVs in the flexible operation workshop conforms to the law of diminishing marginal effectiveness， so as to provide a reference for the configuration of AGVs in the actual manufacturing workshop.

Key words: limited transportation resource, improved non-dominated sorted genetic algorithm-II （improved NSGA-II）, flexible job shop scheduling problem （FJSP）, automatic guided vehicle（AGV）

摘要：

针对智能制造环境中有限自动导引车（AGV）运输资源的柔性作业车间调度问题，以最小化最长完工时间、总能耗和工件的交货期惩罚值为目标，建立有限AGV运输资源的集成调度模型。提出一种改进的非支配排序遗传算法（NSGA-Ⅱ），针对集成调度模型构建三段式编码方案，设计三种初始化规则提高初始种群的质量和多样性。结合关键路径，提出一种改进的变邻域搜索以增强算法的局部搜索能力。实验部分采用多种评价指标与其他算法进行对比，实验结果表明：在不同规模标准测试算例和航空企业实际生产案例下，所提算法均能有效求解有限AGV运输资源的集成调度问题。同时分析不同AGV数量下集成调度模型的有效性，得出柔性作业车间中AGV数量符合边际效应递减规律的结论，为实际制造车间配置AGV提供了参考。

关键词: 有限运输资源, 改进的非支配排序遗传算法, 柔性作业车间调度问题, 自动导引车