A simulation study on the performance of task-determination rules and delivery-dispatching rules for multiple-load AGVs

Y. C. Ho, S. H. Chien

研究成果: 雜誌貢獻期刊論文同行評審

44 引文 斯高帕斯(Scopus)

摘要

In this paper, the control problem of multiple-load automated guided vehicles (AGVs) is studied. A control process that identifies four problems faced by multiple-load AGVs is proposed. The first problem is the task-determination problem, in which a multiple-load AGV determines whether its next task is a pickup task or a delivery task. The second problem is the delivery-dispatching problem, in which a multiple-load AGV determines which delivery point it should visit next if its next task is a delivery task. The third problem is the pickup-dispatching problem, in which a multiple-load AGV determines which pickup point it should visit next if its next task is a pickup task. Finally, the fourth problem is the load-selection problem, which requires a multiple-load AGV to determine which load it should pick up from the output queue of a pickup point. This paper focuses on the first and second problems. Different task-determination rules and delivery-dispatching rules are proposed for these two problems. For the problems that are not the main focus of this study, rules found in the literature or real systems are adopted in this study. The objective of this study is twofold. First, we need to understand how well the proposed rules will perform in different performance measures, e.g. the system's throughput and the mean lateness of parts. Second, we need to understand the mutual effects that different types of rules have on each other, so that the best combination of rules can be identified. Computer simulations were conducted to test the performance of the proposed rules. It is hoped the knowledge learned from this study can be beneficial to real multiple-load AGV systems similar to the one studied here.

原文???core.languages.en_GB???
頁(從 - 到)4193-4222
頁數30
期刊International Journal of Production Research
44
發行號20
DOIs
出版狀態已出版 - 15 10月 2006

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