Bruno, G., Genovese, A. and Piccolo, C. (2014) The capacitated Lot Sizing model: A powerful tool for logistics decision making. International Journal of Production Economics, 155. pp. 380-390. ISSN 0925-5273
Abstract
Starting from the seminal intuitions that led to the developments of the Economic Order Quantity model and of the formulation of the Dynamic Lot Sizing Problem, inventory models have been widely employed in the academic literature and in corporate practice to solve a wide range of theoretical and real-world problems, as, through simple modifications to the original models, it is possible to accommodate and describe a broad set of situations taking place in complex supply chains and logistics systems. The aim of this paper is to highlight, once more, the powerfulness of these seminal contributions by showing how the mathematical formulation of the Capacitated Lot Sizing Problem can be easily adapted to solve some further practical logistics applications (mainly arising in the field of coordination of transportation services) not strictly related to manufacturing and production environment. Mathematical formulations and computational experiences will be provided to support these statements. © 2014 Elsevier B.V. All rights reserved.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014 Elsevier B.V. This is an author produced version of a paper subsequently published in International Journal of Production Economics. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
Keywords: | Lot Sizing; Inventory problems; Logistic decision-making |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 15 Mar 2016 15:28 |
Last Modified: | 20 Mar 2018 23:25 |
Published Version: | http://dx.doi.org/10.1016/j.ijpe.2014.03.008 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.ijpe.2014.03.008 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:96377 |