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Integrated optimisation of operations and financing for large-scale multi-period multi-product capital-constrained supply chains.

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Název: Integrated optimisation of operations and financing for large-scale multi-period multi-product capital-constrained supply chains.
Autoři: Cheng, Junheng1 (AUTHOR), Lin, Yanhong1 (AUTHOR), Cheng, Jingya1 (AUTHOR), Liao, Lingtong1 (AUTHOR), Chu, Feng2 (AUTHOR) feng.chu@univ-evry.fr
Zdroj: International Journal of Production Research. Aug2025, Vol. 63 Issue 15, p5838-5862. 25p.
Témata: *SUPPLY chains, *BUDGET, *HEURISTIC, *INVESTMENT policy, *PROCESS optimization, MIXED integer linear programming
Abstrakt: In a typical supply chain, the operations of procurement, production, inventory, distribution, transportation, and financing decisions are interdependent, collectively impacting the overall performance of the system. However, traditional supply chain management often prioritises minimising operating costs, rarely considering financial strategies simultaneously to achieve enhanced operational benefits. This study addresses a novel operations and financing integrated optimisation problem in multi-period, multi-product, capital-constrained supply chain systems, with the objective of maximising profit. The studied NP-hard problem is formulated as a mixed-integer linear programming (MILP) model. To efficiently and effectively tackle large-sized problems, two decomposition-based effective heuristics are developed. The first decomposes the original problem into two sub-problems: an integrated optimisation problem involving inventory, production, transportation, distribution, and financing (sub-problem 1) and a procurement problem (sub-problem 2), both of which are solved using MILP models. The second method further develops a polynomial-time heuristic for sub-problem 1. To evaluate the performance of the developed methods, 180 instances involving up to 600 products and 1200 raw materials are conducted. Experimental results show that the proposed algorithms can achieve high quality solutions with an average gap of less than 2.24% within 50 seconds. Based on the numerical analysis, managerial insights are discussed. [ABSTRACT FROM AUTHOR]
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Databáze: Business Source Index
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Abstrakt:In a typical supply chain, the operations of procurement, production, inventory, distribution, transportation, and financing decisions are interdependent, collectively impacting the overall performance of the system. However, traditional supply chain management often prioritises minimising operating costs, rarely considering financial strategies simultaneously to achieve enhanced operational benefits. This study addresses a novel operations and financing integrated optimisation problem in multi-period, multi-product, capital-constrained supply chain systems, with the objective of maximising profit. The studied NP-hard problem is formulated as a mixed-integer linear programming (MILP) model. To efficiently and effectively tackle large-sized problems, two decomposition-based effective heuristics are developed. The first decomposes the original problem into two sub-problems: an integrated optimisation problem involving inventory, production, transportation, distribution, and financing (sub-problem 1) and a procurement problem (sub-problem 2), both of which are solved using MILP models. The second method further develops a polynomial-time heuristic for sub-problem 1. To evaluate the performance of the developed methods, 180 instances involving up to 600 products and 1200 raw materials are conducted. Experimental results show that the proposed algorithms can achieve high quality solutions with an average gap of less than 2.24% within 50 seconds. Based on the numerical analysis, managerial insights are discussed. [ABSTRACT FROM AUTHOR]
ISSN:00207543
DOI:10.1080/00207543.2025.2464160