Abstract：It is a common operation mode of shuttle-based storage and retrieval systems (SBS/RS) to combine storage and outbound tasks to form a compound operation. Optimizing a reasonable compound operation path is of great significance for improving operation efficiency and reducing operation costs. In order to improve the order picking efficiency of SBS/RSs, the optimization of the system's compound operation path is attributed to a task assignment problem, and an optimization model is established with the goal of minimizing the total time to complete a batch of tasks. An improved discrete particle swarm optimization (IDPSO) algorithm is designed. The position and velocity of particles and the equation of motion are redefined. Cycle crossover and exchange mutation are introduced into the addition of velocity to achieve fast convergence of the algorithm, while maintaining the diversity of the particle swarm through a repulsion operator, reducing the possibility of falling into a local optimum. The simulation results show that the performance of the algorithm is better than genetic algorithm, which effectively shortens the time of compound operations and improves the picking efficiency.
王姗姗, 张纪会. 穿梭车仓储系统复合作业路径优化[J]. 复杂系统与复杂性科学, 2021, 18(1): 63-72.
WANG Shanshan, ZHANG Jihui. Routing Optimization of Compound Operations in Shuttle-Based Storage and Retrieval Systems. Complex Systems and Complexity Science, 2021, 18(1): 63-72.
[1] 朱由智.穿梭车式密集仓储系统专利技术概述[J]. 物流技术与应用, 2018, 23(6): 134138. Zhu Youzhi. Overview of patented technology of shuttle-type intensive storage system[J]. Logistics & Material Handling, 2018, 23(6): 134138. [2] 任芳.音飞:不断发力智能密集仓储系统—访南京音飞储存设备(集团)股份有限公司产品策划部经理鲁春强[J]. 物流技术与应用, 2017, 22(5): 106108. Ren Fang. Yinfei: Continuously develop intelligent intensive storage system-Interview with Lu Chunqiang, manager of product planning department, Nanjing Yinfei storage equipment (group) Co Ltd[J]. Logistics & Material Handling, 2017, 22(5): 106108. [3] Carlo H J, Vis I F A. Sequencing dynamic storage systems with multiple lifts and shuttles[J]. International Journal of Production Economics, 2012, 140(2): 844853. [4] Lerher T, Ekren B Y, Dukic G, et al. Travel time model for shuttle-based storage and retrieval systems[J]. The International Journal of Advanced Manufacturing Technology, 2015, 78(9): 17051725. [5] Borovinšek M, Ekren B Y, Burinskien A, et al. Multi-objective optimisation model of shuttle-based storage and retrieval system[J]. Transport, 2017, 32(2): 120137. [6] 杨玮,岳婷,刘江, 等. 双载式多层穿梭车仓储系统复合作业路径优化[J]. 计算机集成制造系统, 2018, 24(12): 262272. Yang Wei, Yue Ting, Liu Jiang, et al. Routing optimization for compound operations of double-loading multi-tier shuttle warehousing system[J]. Computer Integrated Manufacturing System, 2018, 24(12): 262272. [7] 方彦军,唐猛. 自动小车存取系统复合作业三维空间路径优化[J]. 计算机集成制造系统,2015, 21(3): 702708. Fang Yanjun,Tang Meng.Three-dimensional rounting optimization for AVS/RS’s composite operation[J]. Computer Integrated Manufacturing System, 2015, 21(3): 702708. [8] 于巧玉,吴耀华,王艳艳. 跨层穿梭车双提升机系统料箱拣选任务调度[DB/OL]. [20200306]. http://kns.cnki.net/kcms/ detail/11.2127.TP.20191213.1146.002.html. Yu Qiaoyu, Wu Yaohua, Wang Yanyan. Tasks scheduling optimization of tier-to-tier shuttle-based storage and retrieval system with double lifts[DB/OL]. [20200306]. http://kns.cnki.net/kcms/detail/11.2127.TP.20191213.1146. 002.html. [9] Azadeh K, De Koster R, Roy D. Robotized and automated warehouse systems: review and recent developments[J]. Transportation Science, 2019, 53(4): 917945. [10] 杨磊,刘会,谢晓飞, 等. 基于指派问题的自动化仓库复合出入库作业优化[J]. 起重运输机械, 2010(11): 2024. Yang Lei, Liu Hui, Xie Xiaofei, et al. Optimization of compound warehouse operation of automatic warehouse based on assignment problem [J]. Hoisting and Conveying Machinery, 2010(11): 2024. [11] 高尚,杨静宇,吴小俊. 求解指派问题的交叉粒子群优化算法[J]. 计算机工程与应用, 2004, 40(8): 5455. Gao Shang, Yang Jingyu, Wu Xiaojun. Using particle swarm optimization algorithm with crossover to solve assignment problem[J]. Computer Engineering and Applications, 2004, 40(8): 5455. [12] 谈文芳,赵强,余胜阳, 等. 改进粒子群优化算法求解任务指派问题[J]. 计算机应用, 2007, 27(12): 28922895. Tan Wenfang, Zhao Qiang, Yu Shengyang, et al. Solving task assignment problem based on improved particle swarm optimization algorithm[J]. Computer Applications, 2007, 27(12): 28922895. [13] 孙晓雅,林焰. 一种新的离散粒子群算法在指派问题中的应用[J]. 计算机应用研究, 2009, 26(11): 40914093, 4097. Sun Xiaoya, Lin Yan. Using new DPSO algorithm to solve assignment problem[J]. Application Research of Computers, 2009, 26(11): 40914093, 4097. [14] Biswas A, Bhunia A K, Shaikh A A. Multi-objective unbalanced assignment problem with restriction of jobs to agents via NSGA-II [J]. International Journal of Mathematics in Operational Research, 2018, 13(1): 107127. [15] 殷人昆,吴阳,张晶炜. 蚁群算法解决指派问题的研究和应用[J]. 计算机工程与科学, 2008, 30(4): 4345. Yin Renkun, Wu Yang, Zhang Jingwei. Research and application of the ant colony algorithm in the assignment problem[J]. Computer Engineering & Science, 2008, 30(4): 4345. [16] 吴艳群,董鹏. 求解大规模不对称指派问题的通用模拟退火算法[J]. 兰州交通大学学报, 2008, 27(4): 149151. Wu Yanqun, Dong Peng. General simulated annealing algorithm for solving large-scale asymmetric assignment[J]. Journal of Lanzhou Jiaotong University, 2008, 27(4): 149151. [17] Kennedy J, Eberhart R C. A discrete binary version of the particle swarm algorithm [C]// 1997 IEEE International conference on systems, man, and cybernetics. Computational cybernetics and simulation. Orlando, FL, USA: IEEE, 1997, 41044108. [18] Clerc M. Discrete Particle Swarm Optimization, Illustrated by the Traveling Salesman Problem[M]//Onwubolu GC,Babu BV. New Optimization Techniques in Engineering. Berlin, Heidelberg: Springer, 2004: 219239. [19] 钟一文,杨建刚,宁正元. 求解TSP问题的离散粒子群优化算法[J]. 系统工程理论与实践, 2006, 26(6): 8894. Zhong Yiwen, Yang Jiangang, Ning Zhengyuan. Discrete particle swarm optimization algorithm for TSP problem[J]. System Engineering Theory & Practice, 2006, 26(6): 8894. [20] 汪定伟,王俊伟,王洪峰. 智能优化方法[M]. 北京: 高等教育出版社. 2007: 3940.
