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Scheduling and routing algorithms for AGVs: A survey

Qiu, Ling, Hsu, Wen-Jing, Huang, Shell-Ying, Wang, Han·2002·International Journal of Production Research

Abstract

Automated guided vehicles (AGVs) are now becoming popular in automated materials handling systems, flexible manufacturing systems and even container handling applications. In the past few decades, much research has been devoted to the technology of AGV systems and rapid progress has been witnessed. As one of the enabling technologies, scheduling and routing of AGVs have attracted considerable attention. Many algorithms for the scheduling and routing of AGVs have been proposed. However, most of the existing results are applicable to systems with a small number of AGVs, offering a low degree of concurrency. With a drastically increased number of AGVs in recent applications (e.g. in the order of a hundred in a container handling system), efficient algorithms are needed to resolve the increased contention of resources (e.g. path, loading and unloading buffers) among AGVs. This survey paper first gives an account of the emergence of the problem of AGV scheduling and routing. It then differentiates it from several related problems and classifies major existing algorithms for the problem. Finally, the paper points out fertile areas for future study of AGV scheduling and routing.

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Metadata

Authors
Qiu, L., Hsu, W.-J., Huang, S.-Y., & Wang, H.
Venue
International Journal of Production Research
Published
2002-01
Volume
40
Issue
3
Pages
745-760
ISSN
  • 0020-7543 (ISSN-L)
  • 1366-588X
OpenAlex
W2140153029
Cited by
402
References
0
FWCI
47.00
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Scheduling and routing algorithms for AGVs: A survey. https://app.cochat.ai/papers/10.1080/00207540110091712
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Qiu, L., Hsu, W.-J., Huang, S.-Y., & Wang, H. (2002). Scheduling and routing algorithms for AGVs: A survey. International Journal of Production Research. https://doi.org/10.1080/00207540110091712

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.