A Hybrid Algorithm for Computing Tours in a Spare Parts Warehouse
作者： Matthias Prandtstetter , Günther R. Raidl , Thomas Misar
DOI: 10.1007/978-3-642-01009-5_3
关键词: Dynamic programming 、 Task (computing) 、 Scheme (programming language) 、 Variable (computer science) 、 Hybrid algorithm 、 Variable neighborhood search 、 Computation 、 Spare part 、 Mathematical optimization 、 Computer science
摘要: We consider a real-world problem arising in warehouse for spare parts. Items ordered by customers shall be collected and this purpose our task is to determine efficient pickup tours within the warehouse. The algorithm we propose embeds dynamic programming computing individual optimal walks through general variable neighborhood search (VNS) scheme. To enhance performance of approach introduce new self-adaptive descent used as local improvement procedure VNS. Experimental results indicate that method provides valuable plans, whereas computation times are kept low several constraints typically stated parts suppliers fulfilled.
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