Abstract
The inbound and outbound tasks for valuable imported ship outfitting items are operated by multiple automated guided vehicles (AGVs) simultaneously in the outfitting warehouse. Given the efficiency mismatch between transportation equipment and the lack of effective scheduling of AGVs, the objective of the studied scheduling problem is to minimize the total travel time cost of vehicles. A multi-AGV task scheduling model based on time window is established considering the loading constraints of AGVs and cooperation time window constraints of stackers. According to the transportation characteristics in the outfitting warehouse, this study proposes a conflict detection method for heavy forklift AGVs, and correspondingly defines a conflict penalty function. Furthermore, to comprehensively optimize travel time cost and conflict penalty, a hybrid genetic neighborhood search algorithm (GA-ANS) is proposed. Five neighborhood structures are designed, and adaptive selection operators are introduced to enhance the ability of global search and local chemotaxis. Numerical experiments show that the proposed GA-ANS algorithm can effectively solve the problem even when the scale of the problem increases and the effectiveness of the vehicle conflict penalty strategy is analyzed.
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Foundation item: China Ministry of Industry and Information Technology for High-Tech Ship Project
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Chen, Y., Jiang, Z. Multi-AGVs Scheduling with Vehicle Conflict Consideration in Ship Outfitting Items Warehouse. J. Shanghai Jiaotong Univ. (Sci.) (2022). https://doi.org/10.1007/s12204-022-2561-z
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DOI: https://doi.org/10.1007/s12204-022-2561-z