Addressing lot sizing and warehousing scheduling problem in manufacturing environment

Authors:
N. Mishra;V. Kumar;N. Kumar;M. Kumar;M. K. Tiwari
Affiliations:
School of Computer Science and Information Technology, University of Nottingham, NG8 1BB, UK;DCU Business School, Dublin City University, Dublin 9, Ireland;School of Management, University of Bath, BA2 7AY, UK;School of Management and Law, Edinburgh Napier University, EH14 1DJ, UK;Department of Industrial Engineering and Management, Indian Institute of Technology, Kharagpur-721302, India
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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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).