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International Journal of Big Data Intelligent Technology, 2023, 4(1); doi: 10.38007/IJBDIT.2023.040103.

Multi-AGV Task Scheduling Method for Intelligent Warehousing

Author(s)

Huiheng Suo, Qiang Hu, Jian Wu, Xie Ma, Youxuan Cai, Shiai Bi, Jingwen Zhang, Xiushui Ma

Corresponding Author:
Jian Wu
Affiliation(s)

Nanchang Hangkong University, Nanchang, China

Abstract

For the collaborative control of automatic guided vehicles (AGVs) in logistics and warehousing, task scheduling is critical for improving the efficiency of AGV execution. To address this issue, this paper first establishes a mathematical model for multi-task AGV task scheduling and proposes an efficiency evaluation index. Then, a particle swarm optimization (PSO) based order task scheduling algorithm is proposed. This algorithm assigns matching values to sort stations based on orders, and then sorting stations allocate tasks to AGVs. Finally, simulation results show that this algorithm effectively coordinates the operation of the entire intelligent warehouse, verifying the correctness of the algorithm and providing a solution for practical warehouse task scheduling problems.

Keywords

Intelligent Storage, AGV, Task Scheduling, PSO

Cite This Paper

Huiheng Suo, Qiang Hu, Jian Wu, Xie Ma, Youxuan Cai, Shiai Bi, Jingwen Zhang, Xiushui Ma. Multi-AGV Task Scheduling Method for Intelligent Warehousing. International Journal of Big Data Intelligent Technology (2023), Vol. 4, Issue 2: 17-25. https://doi.org/10.38007/IJBDIT.2023.040103.

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