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Addressing lot sizing and warehousing scheduling problem in manufacturing environment

Mishra, N.; Kumar, V.; Kumar, N.; Kumar, M.; Tiwari, M. K.

Authors

V. Kumar

N. Kumar

M. Kumar

M. K. Tiwari



Abstract

In recent years, lot sizing issues have gained attention of researchers worldwide. Previous studies devoted on lot sizing scheduling problems were primarily focused within the production unit in a manufacturing plant. In this article lot sizing concept is explored in the context of warehouse management. The proposed formulation helps manufacturer to decide the effective lot-size in order to meet the due dates while transferring the product from manufacturer to retailer through warehouse. A constrained based fast simulated annealing (CBFSA) algorithm is used to effectively handle the problem. CBFSA algorithm encapsulates the salient features of both genetic algorithm (GA) and simulated annealing (SA) algorithms. This hybrid solution approach possesses the mixed characteristics of both of the algorithms and determines the optimal/near optimal sequence while taking into consideration the lot-size. Results obtained after implementing the proposed approach reveals the efficacy of the model over various problem dimensions and shows its superiority over other approaches (GA and SA). © 2011 Elsevier Ltd. All rights reserved.

Citation

Mishra, N., Kumar, V., Kumar, N., Kumar, M., & Tiwari, M. K. (2011). Addressing lot sizing and warehousing scheduling problem in manufacturing environment. Expert Systems with Applications, 38(9), 11751-11762. https://doi.org/10.1016/j.eswa.2011.03.062

Journal Article Type Article
Online Publication Date Mar 11, 2011
Publication Date Jan 1, 2011
Deposit Date Jun 8, 2022
Journal Expert Systems with Applications
Print ISSN 0957-4174
Electronic ISSN 0957-4174
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 38
Issue 9
Pages 11751-11762
DOI https://doi.org/10.1016/j.eswa.2011.03.062
Keywords Warehousing; GA; SA; Tardiness; Lot-sizing; Scheduling
Public URL https://hull-repository.worktribe.com/output/3614042



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