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Integrated supply chain plan under multiple distribution networks: an implementation of mixed integer linear programming

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  • Rizwan Shoukat

    (Southwest Jiaotong University
    National Engineering Laboratory of Integrated Transportation Big Data Application Technology
    Lab of National United Engineering Laboratory of Integrated and Intelligent Transportation)

Abstract

The study aims to minimize the cost of operations, storage, penalties, and dispatch in one of the largest paper and board manufacturing industries in Asia. The real-world data is obtained for cases underneath mixed products' in integrated and non-integrated supply chains. The cost minimization problem is formulated by developing the mixed integer linear programming (MILP) model constraining the multiple origins and destination ports in Pakistan. The metaheuristic optimization technique, such as the multi-objective genetic algorithm (MOGA), is applied based on epsilon dominance. The study results demonstrate that the cost of an integrated supply chain is minimal under various circumstances compared to the non-integrated supply chain, which provides a difference of 37% in both. Further, this study integrates the supply of paper and board products with the intermodal and multimodal transportation networks to investigate the most feasible supply chain network in the South Asian region.

Suggested Citation

  • Rizwan Shoukat, 2024. "Integrated supply chain plan under multiple distribution networks: an implementation of mixed integer linear programming," Circular Economy and Sustainability, Springer, vol. 4(4), pages 2599-2623, December.
    • Handle: RePEc:spr:circec:v:4:y:2024:i:4:d:10.1007_s43615-024-00404-3
    DOI: 10.1007/s43615-024-00404-3
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