基于混合算法的自动导引车调度问题研究  

Research on automated guided vehicle scheduling problem based on hybrid algorithm

作　　者：屈新怀[1] 严飞 丁必荣[1] 孟冠军[1] QU Xinhuai;YAN Fei;DING Birong;MENG Guanjun(School of Mechanical Engineering,Hefei University of Technology,Hefei 230009,China)

机构地区：[1]合肥工业大学机械工程学院,安徽合肥230009

出　　处：《合肥工业大学学报（自然科学版）》2023年第6期732-737,共6页Journal of Hefei University of Technology：Natural Science

基　　金：国家重点研发计划资助项目(2019YFB1705303)。

摘　　要：针对自动化仓库自动导引车(automated guided vehicle,AGV)调度问题,文章在考虑车辆载重约束的情况下,建立车辆行驶总距离和总能耗最小为目标的数学模型,并通过离散差分进化算法与蚁群算法相结合的混合算法进行求解。将混合算法与改进蚁群算法、遗传算法、模拟退火算法、粒子群算法在CVRPLIB SET P算例集上的求解结果进行对比,验证该混合算法的有效性;通过数值仿真实验对提出的自动化分拣仓库AGV调度问题进行求解,证明该混合算法对实际算例有较好的求解结果,可以有效提高自动化仓库作业效率。In order to solve the problem of automated guided vehicle(AGV)scheduling in automated warehouse,a mathematical model was established to minimize the total distance and total energy consumption of vehicles under the condition of vehicle load constraint,and it was solved by a hybrid algorithm combining discrete differential evolution algorithm and ant colony algorithm.The results of the hybrid algorithm on CVRPLIB SET P were compared with those of the improved ant colony algorithm,genetic algorithm,simulated annealing algorithm and particle swarm optimization algorithm to verify the effectiveness of the hybrid algorithm.The problem of AGV scheduling in automated warehouse was solved by numerical simulation,and the results of practical examples were satisfactory.The hybrid algorithm can effectively improve the operating efficiency of automated warehouse.

关 键 词：自动导引车(AGV) 任务调度 蚁群算法 离散差分进化算法 能耗 

分 类 号：TP273.5[自动化与计算机技术—检测技术与自动化装置]