Model and solution approaches for retrieval operations in a multi-tier shuttle warehouse system

[Display omitted] •The sequence of retrieval requests to minimize the makespan.•A mixed integer programming model is developed for the retrieval scheduling problem.•Several heuristic algorithms are designed to solve the heuristic algorithm.•Algorithms for solving different data sizes for Multi-tier...

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Bibliographic Details
Published in:	Computers & industrial engineering Vol. 141; p. 106283
Main Authors:	Wang, Yanyan, Liu, Ziwei, Huang, Ke, Mou, Shandong, Zhang, Rongxu
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.03.2020
Subjects:	Heuristics Mixed integer programming model Multi-tier shuttle warehousing system Retrieval task scheduling Multi-tier shuttle warehousing system Heuristics Retrieval task scheduling Mixed integer programming model
ISSN:	0360-8352, 1879-0550
Online Access:	Get full text
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Summary:	[Display omitted] •The sequence of retrieval requests to minimize the makespan.•A mixed integer programming model is developed for the retrieval scheduling problem.•Several heuristic algorithms are designed to solve the heuristic algorithm.•Algorithms for solving different data sizes for Multi-tier Shuttle Warehouse System. In the Multi-tier Shuttle Warehousing System (MSWS), shuttles are responsible for horizontal movements and lifts are responsible for vertical movements. In this paper, a retrieval task scheduling problem for a tier-captive MSWS under single command cycle is considered. This paper aims to determine the sequence of retrieval tasks to minimize the makespan. A mixed integer programming model is developed for the retrieval task scheduling problem. When the number of tasks is less than 10, the mixed integer programming model can be solved by the GUROBI solver to find the exact solutions within a short period. Moreover, a tabu search algorithm, an ant colony algorithm and a simulated annealing algorithm are designed and applied to solve large size problems with up to 200 tasks. By analyzing experimental results, the ant colony algorithm shows stable and superior performance in solving large size problems.
ISSN:	0360-8352 1879-0550
DOI:	10.1016/j.cie.2020.106283