文章基本信息

标题：The scheduling of automatic guided vehicles for the workload balancing and travel time minimi-zation in the flexible manufacturing system by the nature-inspired algorithm
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作者：V.K. Chawla ; A. K. Chanda ; Surjit Angra 等
期刊名称：Journal of Project Management
印刷版ISSN：2371-8366
电子版ISSN：2371-8374
出版年度：2018
卷号：4
期号：1
页码：19-30
DOI：10.5267/j.jpm.2018.8.001
出版社：Growing Science
摘要：The real-time scheduling of automatic guided vehicles (AGVs) in flexible manufacturing system (FMS) is observed to be highly critical and complex due to the dynamic variations of production requirements such as an imbalance of AGVs loading, the high travel time of AGVs, variation in jobs, and AGV routes to name a few. The output from FMS considerably depends on the effi-cient scheduling of AGVs in the FMS. The multi-objective scheduling decisions for AGVs by nature inspired algorithms yield a considerable reduction throughput time in the FMS. In this paper, investigations are carried out for the multi-objective scheduling of AGVs to simultaneously balance the workload of AGVs and to minimize the travel time of AGVs in the FMS. The multi-objective scheduling is carried out by the application of nature-inspired grey wolf optimization algorithm (GWO) to yield a balanced workload for AGVs and also to minimize the travel time of AGVs simultaneously in the FMS. The output yield of the GWO algorithm is compared with the results of benchmark problems from the literature. The resulting yield of the proposed algorithm for the multi-objective scheduling of AGVs is observed to outperform the existing algorithms for scheduling of AGVs.
关键词：Automatic guided vehicles; Flexible manufacturing system; Grey wolf optimization algorithm; Simultaneous scheduling