Multi-objective AGV scheduling in an automatic sorting system of an unmanned

Automated guided vehicle (AGV) is a logistics transport vehicle with high safety performance and excellent availability, which can genuinely achieve unmanned operation. The use of AGV in intelligent warehouses or unmanned warehouses for sorting can improve the efficiency of warehouses and enhance th...

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Bibliographic Details
Published in:PloS one 2019-12, Vol.14 (12), p.e0226161
Main Authors: Liu, Yubang, Ji, Shouwen, Su, Zengrong, Guo, Dong, Wang, Yong
Format: Article
Language:English
Subjects:
Algorithms
Automatic guided vehicles
Warehouses
Online Access:Get full text
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Summary:Automated guided vehicle (AGV) is a logistics transport vehicle with high safety performance and excellent availability, which can genuinely achieve unmanned operation. The use of AGV in intelligent warehouses or unmanned warehouses for sorting can improve the efficiency of warehouses and enhance the competitiveness of enterprises. In this paper, a multi-objective mathematical model was developed and integrated with two adaptive genetic algorithms (AGA) and a multi-adaptive genetic algorithm (MAGA) to optimize the task scheduling of AGVs by taking the charging task and the changeable speed of the AGV into consideration to minimize makespan, the number of AGVs used, and the amount of electricity consumption. The numerical experiments showed that MAGA is the best of the three algorithms. The value of objectives before and after optimization changed by about 30%, which proved the rationality and validity of the model and MAGA.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0226161