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Assignment of duplicate storage locations in distribution centres to minimise walking distance in order picking

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posted on 2020-06-22, 08:55 authored by W Jiang, Jiyin LiuJiyin Liu, Y Dong, L Wang
© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group. With the rapid development of e-commerce, the orders processed in B2C warehouses are characterised by heterogeneous and small volume. The traditional storage assignment strategies used in the picker-to-parts warehouses do not have advantage any more. In this case, the scattered storage strategy is a good alternative. In this paper, we study a new scattered storage strategy that allows the same product to be placed in multiple storage locations. The correlation between products which reflects how frequently any two products will be ordered together in the same order is considered. The problem is formulated as a 0-1 integer programming model to minimise the weighted sum of distances between the products, with weight being the elements of the correlation matrix. To solve large-scale problems, a GA and a basic PSO algorithm are developed. To improve solution quality, a new PSO algorithm based on the problem characteristic is designed and a hybrid algorithm combing it with GA is proposed. Experiments show that the solutions of these algorithms are close to the optimal solutions for the small-sale problems. For larger problems, the specially designed new PSO greatly improves solution quality as compared to the basic algorithms and the hybrid algorithm makes further improvement.

Funding

China Scholarships Council (No.201808330034)

National Natural Science Foundation of China (71472081)

Fund for Innovative Research Group of the National Natural Science Foundation of China (71621061)

Major International Joint Research Project of the National Natural Science Foundation of China (71520107004)

111 Project (B16009)

History

School

  • Business and Economics

Department

  • Business

Published in

International Journal of Production Research

Publisher

Taylor and Francis

Version

  • AM (Accepted Manuscript)

Rights holder

© Taylor and Francis

Publisher statement

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 28 May 2020, available online: https://doi.org/10.1080/00207543.2020.1766714

Acceptance date

2020-05-02

Publication date

2020-05-28

ISSN

0020-7543

eISSN

1366-588X

Language

  • en

Depositor

Prof Jiyin Liu. Deposit date: 21 June 2020

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