自动导向小车与加工设备多目标集成调度的聚类遗传算法  

Clustering Genetic Algorithm for Multi-objective Integrated Scheduling of AGVs and Machine

作　　者：邹裕吉 宋豫川[1] 王馨坤 王毅[1] ZOU Yuji;SONG Yuchuan;WANG Xinkun;WANG Yi(State Key Laboratory of Mechanical Transmission,Chongqing University,Chongqing,400044)

机构地区：[1]重庆大学机械传动国家重点实验室,重庆400044

出　　处：《中国机械工程》2022年第1期97-108,共12页China Mechanical Engineering

基　　金：国家自然科学基金(51205429);重庆市科技局重庆市技术创新与应用示范专项(cstc2018jszx-cyzdX0150,cstc2018jszx-cyzdX0187)。

摘　　要：针对AGV与加工设备的集成调度问题,在考虑AGV无冲突路径规划的情况下,建立了以最大完工时间、AGV运行时间及机器总负荷为优化目标的调度优化模型,提出一种基于时间窗和Dijkstra算法的多目标自适应聚类遗传算法。根据算法在不同迭代时期的特点,提出一种包含自适应个体交叉概率的交叉重组策略;设计了自适应种群变异概率;引入基于网格划分数和扩容网格距离的环境选择策略。仿真结果验证了算法的可行性和优越性。Aiming at the integrated scheduling problems of AGV and processing equipment and considering the conflict-free path planning of AGV,a scheduling optimization model was established based on the maximum completion time,AGV running time,and total machine load.And a scheduling optimization model was proposed based on time window and Dijkstra's multi-objective adaptive clustering genetic algorithm.According to the characteristics of the algorithm in different iteration periods,a cross-recombination strategy including adaptive individual cross-probability was proposed.Adaptive population mutation probability was designed.An environmental selection strategy was introduced based on the number of grid divisions and the distances of the expanded grid.The simulation results verified the feasibility and superiority of the algorithm.

关 键 词：自动导向小车多目标优化 聚类 机器人运动路径规划 生产调度 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] TH187[自动化与计算机技术—控制科学与工程]