A Robust Approach for Improving Computational Efficiency of Order-Picking Problems

doi:10.1007/11552451_139

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题名:	A Robust Approach for Improving Computational Efficiency of Order-Picking Problems
作者:	Chiang, Yu-Min;Chen, Shih-Hsin;Wu, Kuo-Chang
关键词:	Tabu Search;Fuzzy Modeling;Fuzzy Inference System;Distribution Center;Order Picking
日期:	2005-09
上传时间:	2021-10-07 12:10:47 (UTC+8)
出版者:	Springer
摘要:	The new market forces have affected the operation of distribution centers (DCs) extremely. The DCs demand an increased productivity and a low cost in their daily operation. This paper focuses on the order-picking operation, which is the core operation of DCs, to improve the material-handling process and enhance the competitiveness. The study applied an integrated framework that combined two algorithms, branch-and-bound and tabu search, to the order-picking problem and developed a neighborhood selection criterion based on constraint propagation and the prune-and-search algorithm to improve computational efficiency. The proposed method forbids bad node when searching a solution by branch-and-bound algorithm or tabu search. Besides, in order to make the algorithm more robust and reasonable, the fuzzy modeling was employed. The empirical result shows the approach decreases the computational effort effectively on the both algorithms. The study may be of interest for the researchers in the optimization of DCs’ operations and the DCs’ managers.
關聯:	Lecture Notes in Computer Science 3682, p.1007-1014
DOI:	10.1007/11552451_139
显示于类别:	[資訊工程學系暨研究所] 期刊論文

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