穿梭车自动存取系统任务调度算法适配性研究  被引量:3

Adaptability of task scheduling algorithm for shuttle-based storage and retrieval system

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作  者:刘刚 王艳艳[1] 黄珂 满荣军[3] 吴耀华 LIU Gang;WANG Yanyan;HUANG Ke;MAN Rongjun;WU Yaohua(Shenzhen Research Institute, Shandong University, Shenzhen 518000, China;School of Mechanical Engineering, Shandong University, Jinan 250061, China;School of Control Science and Engineering, Shandong University, Jinan 250061, China)

机构地区:[1]山东大学深圳研究院,广东深圳518000 [2]山东大学机械工程学院,山东济南250061 [3]山东大学控制科学与工程学院,山东济南250061

出  处:《计算机集成制造系统》2022年第5期1435-1448,共14页Computer Integrated Manufacturing Systems

基  金:深圳市科技创新委员会面上基金资助项目(JCYJ20190807094803721);山东省自然科学基金面上资助项目(ZR2020MF085);山东省自然科学基金重点资助项目(ZR2020KF027)。

摘  要:多层穿梭车自动存取系统集存储和拣选功能于一体,利用高层货架实现货物密集存储,穿梭车、提升机等多设备并行作业。多层穿梭车自动存取系统作业效率较高,但是设备调度方案与配置参数等因素均会影响系统性能。通过剖析多层穿梭车自动存取系统的工作流程和设备服务时间,研究穿梭车和提升机并行工作的约束规则,建立了以出库时间最小为优化目标的混合整数规划模型。在模型求解方面上,分别使用禁忌搜索算法、遗传算法改进了蚁群算法,并提出一种Gurobi与启发式算法结合的求解新思路,经过实验验证,求解精度和求解效率有较大提升。最后,通过计算不同的任务规模实例分析了3种改进算法的求解性能,建立了一套出库任务规模与精确求解的适配方案,减少了系统订单作业时间,提高了系统作业效率。A shuttle-based storage and retrieval system(SBS/RS)integrates the functions of storage and order picking,had higher operational efficiency.But the system performance may be affected by the scheduling strategy and various parameter settings between devices.Through analyzing the SBS/RS's workflow and computing the service time of equipments,a mixed integer programming model aiming at minimizing the total outbound time was established.As for model solving,the improved ant colony algorithm with tabu search and genetic algorithm were proposed to solve the model separately.At the same time,the heuristic algorithms were combined with Gurobi tools to obtain exact solutions quickly.By analyzing the bottleneck of each improved algorithm,an adaptability scheme between the task scale and the optimal solution was established,which provided strategy for the efficient solution of the task scheduling problem,reduced the order operation time and improved the operation efficiency.

关 键 词:多层穿梭车自动存取系统 任务调度 禁忌搜索算法 遗传算法 改进蚁群算法 算法适配 

分 类 号:TP278[自动化与计算机技术—检测技术与自动化装置]

 

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