基于改进非支配排序遗传算法的多负载AGV任务调度研究  

Research on Multi-Load AGV Task Scheduling Based on Improved Non-Dominated Sort Genetic Algorithm

作　　者：汪莉 李兵 WANG Li;LI Bing(College of Information Engineering and Artificial Intelligence,Lanzhou University of Finance and Economics,Lanzhou 730020,China)

机构地区：[1]兰州财经大学信息工程与人工智能学院,甘肃兰州730020

出　　处：《物流工程与管理》2024年第9期28-30,35,共4页Logistics Engineering and Management

摘　　要：以某中小型物流配送中心进行仿真实验,以可使用AGV数量、订单任务对应的订单货架货物数量为变量,开展四个子实验。结果显示,每个子实验的优化目标随迭代次数的变化趋势都比较符合预期,随着种群每一代的更新,除了整体呈现下降且收敛的趋势外,算法在求解模型时努力尝试跳脱出局部最优。A simulation experiment was conducted on a small and medium-sized logistics distribution center,with the number of AGVs available and the quantity of goods on the order shelves corresponding to the order tasks as variables.Four sub experiments were carried out.The results showed that the optimization objectives of each sub experiment showed a relatively consistent trend with the number of iterations.As the population was updated in each generation,in addition to the overall decreasing and converging trend,the algorithm attempted to escape from local optima when solving the model.

关 键 词：多目标 快速非支配排序 遗传算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] TH165.1[自动化与计算机技术—计算机科学与技术]