魔方型智能仓储系统多AGV任务调度及优化  

Multi-AGV Task Scheduling and Optimization of Cube-based Intelligent Warehouse System

作　　者：杨春霞[1] 陈航慧 师浩森 YANG Chunxia;CHEN Hanghui;SHI Haosen(School of Vehicle and Transportation Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China)

机构地区：[1]太原科技大学车辆与交通工程学院,山西太原030024

出　　处：《物流科技》2024年第11期174-178,共5页Logistics Sci-Tech

基　　金：太原科技大学研究生教育创新项目(SY2022067);太原科技大学研究生联合培养示范基地项目(J2022020);太原科技大学教学改革创新项目(JG202273)。

摘　　要：为探究针对魔方型仓储系统的多AGV调度问题,建立考虑倒箱因素的多AGV调度优化数学模型,设计改进的多层编码的遗传算法,有助于算法跳出局部最优并改善其局部搜索能力。通过设计不同算例,对比优化前后的AGV调度方案,验证改进算法的有效性和可行性,同时,对不同任务规模、AGV规模、仓储填充率、仓储立体规模和仓储平面规模五方面的工况进行探究分析,为魔方型仓储系统运行状况研究提供理论基础。In order to explore the multi-AGV scheduling problem for the Rubik's cube storage system,establish a multi-AGV scheduling optimization mathematical model considering the factor of the box,and design an improved multi-layer coding genetic algorithm,which is helpful for the algorithm to jump out of the local optimum and improve its local search capability,through designing standard examples,comparing the AGV scheduling scheme before and after optimization,and verifying the effectiveness and feasibility of the improved algorithm.The working conditions are explored and analyzed,which provides a theoretical basis for the research on the operation status of the Rubik's cube storage system.

关 键 词：魔方型仓储 AGV任务分配 改进遗传算法 

分 类 号：F406.5[经济管理—产业经济]