摘要
针对多自动导引车(automated guided vehicle,AGV)系统任务分配中因未考虑负载能力差异,导致AGV负载利用率低、任务完成耗时长的问题,提出一种新的任务分配策略。该策略充分考虑AGV负载能力差异,使负载利用率高的AGV获得优先指派权,允许各AGV以组合运输任务的方式并行处理多个任务,从而达到系统处理运输任务的效率最优。为了设计求解该策略的遗传算法,采用整数编码的方式简化遗传算法的解码过程并以AGV负载能力差异为约束生成初始种群,通过算例分析该策略的决策结果及效率。结果表明:基于AGV负载能力差异化的任务分配策略在不同运输任务总质量情形下,AGV平均负载利用率高于94%且方差最大为0.01;在不同任务质量比例情形下,AGV平均负载利用率高于96%且方差最大为0.16。与传统遗传算法、文化混合算法以及改进迭代局部搜索算法相比,文中方法下AGV完成任务时间最大减少了42.86%,AGV平均负载利用率最大提高了81.8%。
In order to solve the problem of low AGV load utilization rate and long task completion time due to the lack of consideration of load capacity difference in the task allocation of multiple automated guided vehicle(AGV)system,a new task allocation strategy was proposed.This strategy fully considered the difference in the load capacity of AGVs,so that AGVs with high load utilization rate could obtain priority assignment rights,and allowed each AGV to process multiple tasks in parallel in the form of combined transportation tasks,so as to achieve the optimal efficiency of the system in handling transportation tasks.In order to design the genetic algorithm to solve the strategy,the integer coding method was used to simplify the decoding process of the genetic algorithm and the initial population was generated based on the difference in AGV load capacity,the decision-making results and efficiency of the strategy were analyzed through a case study.The results show that the average load utilization rate of AGV is higher than 94%and the maximum variance is 0.01 under the case of total weight of different transportation tasks,and the average load utilization rate of AGV is higher than 96%and the maximum variance is 0.16 under the case of different task weight proportions.Compared with the traditional genetic algorithm,cultural mixing algorithm and improved iterative local search algorithm,the task completion time of AGV is reduced by 42.86%and the average load utilization rate of AGV is increased by 81.8%in the paper′s method.
作者
宋栓军
张家豪
宋嘉轩
SONG Shuanjun;ZHANG Jiahao;SONG Jiaxuan(School of Mechanical and Electrical Engineering,Xi’an Polytechnic University,Xi’an 710048,China;Business School,Shaoguan University,Shaoguan 512005,Guangdong,China)
出处
《西安工程大学学报》
2025年第4期17-25,36,共10页
Journal of Xi’an Polytechnic University
基金
陕西省重点研发计划项目(2021GY-337)。
关键词
多自动导引车(AGV)系统
任务分配
负载利用率
单次多任务
分配策略
multiple automated guided vehicle(AGV)system
task allocation
load utilization
single-occurrence multitasking
allocation strategy
作者简介
通信作者:宋栓军(1974-),男,教授,博士,研究方向为多AGV系统生产调度。E-mail:z1260752229@outlook.com。
