首页|自动分拣仓库中多载量AGV调度与路径规划算法

自动分拣仓库中多载量AGV调度与路径规划算法

扫码查看
原文链接
  • 万方数据
  • 维普
在自动分拣仓库中,多载量自动导引小车(AGV)具有强运输能力,但其多载量特征也增加了调度与路径规划的复杂性.针对多载量AGV调度与路径规划的协同优化问题,以最小化最大搬运完成时间为目标,建立了该问题的混合整数线性规划模型,并提出一种聚类-协同优化算法.算法首先定义了包裹相似度,设计聚类算法划分包裹组,使每个包裹组可由多载量AGV在一次作业中完成分拣;进而针对问题的多决策特征,设计协同进化遗传算法对包裹组进行指派和排序,并将无冲突路径规划算法引入到协同进化遗传算法的解码方案中,用以搜索最优路径并解决多AGV路径冲突,从而实现了多载量AGV调度与路径规划的协同优化.通过不同问题规模的仿真实验验证了所提算法的高效性和稳定性.
Multi-load AGVs scheduling and routing algorithm in automatic sorting warehouse
In an automatic sorting warehouse,the multi-load AGV has strong transportation capacity,but its multi-load characteristic also increases the complexity of scheduling and routing.Aiming at the collaborative optimization problem of multi-load AGVs scheduling and routing,a mixed integer linear programming model was established with the goal of mini-mizing the maximum handling completion time.Then,a Clustering-Collaborative Optimization Algorithm(CCOA)was proposed.Firstly,the package similarity was defined,and a clustering algorithm was designed to divide the packages into several groups,so that the packages contained in each group could be sorted by a multi-load AGV in one operation trip.Furthermore,according to the multi-decision characteristics of the problem,a Co-evolutionary Genetic Glgo-rithm(CGA)was designed to assign and sort the divided groups,and the conflict-free routing algorithm designed was embedded in CGA to search the optimal route and resolve the conflicts between multiple AGVs,so as to achieve the collaborative optimization of multi-load AGVs scheduling and routing.Extensive simulation experiments with different problem scales were carried out to verify the efficiency and stability of the proposed algorithm.

multi-load automated guided vehicleschedulingroutingcollaborative optimizationautomatic sorting warehouse

余娜娜、李铁克、张文新、袁帅鹏、张卓伦、王柏琳

展开 >

郑州航空工业管理学院 管理工程学院,河南 郑州 450046

北京科技大学经济管理学院,北京 100083

钢铁生产制造执行系统技术教育部工程研究中心,北京 100083

多载量自动导引小车 调度 路径规划 协同优化 自动分拣仓库

国家自然科学基金国家自然科学基金教育部人文社会科学研究青年基金北京市自然科学基金中央高校基本科研业务费专项河南省科技攻关计划

723010267123100117YJC6301439174038FRF-BD-20-16A242102220039

2024

10.13196/j.cims.2022.0087

计算机集成制造系统
中国兵器工业集团第210研究所

计算机集成制造系统

CSTPCD北大核心
影响因子：1.092
ISSN：1006-5911
年,卷(期)：2024.30(4)
  • 7