Scheduling and path planning of multiple automatic guided vehicles in container terminals

被引：0
|
作者：
Li J. [1 ]
Zhu X. [1 ,2 ]
机构：
[1] College of Arts and Sciences, Shanghai Maritime University, Shanghai
[2] Institute of Logistics and Engineering, Shanghai Maritime University, Shanghai
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2022年 / 28卷 / 05期
关键词：
Automated container terminal; Conflict prevention; Floyd algorithm; Grey wolf optimizer algorithm; Multiple automatic guided vehicle scheduling; Path planning;
D O I：
10.13196/j.cims.2022.05.016
中图分类号：
学科分类号：
摘要：
Aiming at the scheduling and path planning of multiple Automated Guided Vechicles (AGVs) on automated container terminals, a mathematical model with the goal of minimizing AGV energy consumption was established by considering AGV load and conflicts. Two stages algorithm was designed to solve this model. In the first stage, Grey Wolf Optimizer (GWO) was used to optimize AGV scheduling under the shortest path based on task combination decomposition. In the second stage, for the better AGV scheduling, Floyd based time conflict prediction algorithm was further used to optimize its path to achieve the result of conflict prevention. Experiments verified the feasibility and effectiveness of the designed algorithm under different problem scales. The results showed that the proposed algorithm could effectively reduce the code length, and the result quality, running time and convergence were better than those obtained by other algorithms. It could effectively solve the scheduling of multiple AGVs under different scales and prevent conflict path planning, and reduce the energy consumption of AGVs. © 2022, Editorial Department of CIMS. All right reserved.
引用
收藏
页码：1449 / 1461
页数：12
相关论文
共 29 条
  • [1] YANG Yongsheng, FENG Youyong, LIANG Chengji, Et al., Integrated scheduling of automated guided vehicles and rail-mounted gantry cranes at automated container terminals, Journal of Shanghai Maritime University, 38, 2, pp. 1-6, (2017)
  • [2] ZHAO Q R, JI S W, GUO D, Et al., Research on cooperative scheduling of automated quayside cranes and automatic guided vehicles in automated container terminal, Mathematical Problems in Engineering, 2019, (2019)
  • [3] ZHONG M S, YANG Y S, ZHOU Y M, Et al., Adaptive autotuning mathematical approaches for integrated optimization of automated container terminal, Mathematical Problems in Engineering, 2019, (2019)
  • [4] CHEN X C, HE S W, ZHANG Y X, Et al., Yard crane and AGV scheduling in automated container terminal: A multi-robot task allocation framework, Transportation Research Part C: Emerging Technologies, 114, pp. 241-271, (2020)
  • [5] MA X Y, BIAN Y M, GAO F, Et al., An improved shuffled frog leaping algorithm for multiload AGV dispatching in automated container terminals, Mathematical Problems in Engineering, 2020, (2020)
  • [6] LIU Erhui, YAO Xifan, TAO Tao, Et al., Integrated AGV job shop scheduling based on improved flower pollination algorithm, Computer Integrated Manufacturing Systems, 25, 9, pp. 2219-2236, (2019)
  • [7] FAZLOLLAHTABAR H, SAIDI-MEHRABAD M, BALAKRISHNAN J., Mathematical optimization for earliness/tardiness minimization in a multiple automated guided vehicle manufacturing system via integrated heuristic algorithms, Robotics and Autonomous Systems, 72, pp. 131-138, (2015)
  • [8] JIN J, ZHANG X H., Multi AGV scheduling problem in automated container terminal, Journal of Marine Science and Technology, 24, 1, pp. 32-38, (2016)
  • [9] MOUSAVI M, YAP H J, MUSA S N, Et al., Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization, PLoS One, 12, 3, (2017)
  • [10] LIU Y B, JI S W, SU Z R, Et al., Multi-objective AGV scheduling in an automatic sorting system of an unmanned (intelligent) warehouse by using two adaptive genetic algorithms and a multi-adaptive genetic algorithm, PLoS One, 14, 12, (2019)
123