Shbool, Mohammad A., Al-Bazi, Ammar and Bashabsheh, Nibal Al (2024). A Mathematical Model for Potash Supply Chain Management with a Strategic Logistics Perspective. IMA Journal of Management Mathematics ,
Abstract
This paper introduces a novel Integer Linear Programming (ILP) model designed to enhance the efficiency and sustainability of the Potash supply chain, a crucial element supporting global agriculture. The developed mathematical optimisation model focuses on fleet selection (private/outsource) and incorporates the concept of "inter-warehouse collaboration," which addresses key logistics considerations. Integrating mining, processing, storage, and transportation, the model encompasses decision variables like extracted carnallite amount, production, storage levels, and shipped Potash amount. Illustrated through a case study on the Arab Potash Company (APC) in Jordan, the results showcase the model's proficiency in meeting local and international market demands. The model ensures resilient and sustainable supply chain performance by emphasising logistics optimisation, particularly in fleet selection. The study attains the highest "warehouse-to-warehouse" support for Standard and Granular potash types in the international demand scenario, contributing to efficient production planning and fleet management. In conclusion, the presented mathematical model is a valuable tool for Potash industry stakeholders, offering insights for strategic decision-makers involved in production planning and fleet management.
Publication DOI: | https://doi.org/10.1093/imaman/dpae028 |
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Divisions: | College of Business and Social Sciences > Aston Business School College of Business and Social Sciences > Aston Business School > Operations & Information Management College of Business and Social Sciences Aston University (General) |
Additional Information: | Copyright © 2024 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). |
Publication ISSN: | 1471-6798 |
Last Modified: | 25 Oct 2024 07:38 |
Date Deposited: | 23 Oct 2024 10:22 |
Full Text Link: | |
Related URLs: |
https://academi ... dpae028/7824247
(Publisher URL) |
PURE Output Type: | Article |
Published Date: | 2024-10-16 |
Published Online Date: | 2024-10-16 |
Accepted Date: | 2024-10-15 |
Authors: |
Shbool, Mohammad A.
Al-Bazi, Ammar ( 0000-0002-5057-4171) Bashabsheh, Nibal Al |