Trade credit and loan in capital-constrained supply chain network design model.
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| Title: | Trade credit and loan in capital-constrained supply chain network design model. |
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| Authors: | Fathi Heli Abadi, Azar1 (AUTHOR) a_fathiheliabadi@sbu.ac.ir, Raad, Abbas1 (AUTHOR) a-raad@sbu.ac.ir, Motameni, Alireza1 (AUTHOR) A_Motameni@sbu.ac.ir, Talebi, Davood1 (AUTHOR) d-talebi@sbu.ac.ir |
| Source: | Environment, Development & Sustainability. Feb2025, Vol. 27 Issue 2, p5187-5222. 36p. |
| Subject Terms: | *Stockholder wealth, *Multi-objective optimization, *Net present value, *Supply chains, *Small business, *Particle swarm optimization |
| Abstract: | Enhancing the management of working capital in supply chains due to fluctuations in demand necessitates the utilization of financial resources such as loans and trade credit. Small and medium-sized enterprises in developing countries often face financial challenges and lack the necessary credit history to secure bank loans. Consequently, trade credit has emerged as a viable debt-based financing alternative. This article presents a two-objective mathematical model for a three-level, multi-period, multi-product supply chain network, in which suppliers provide trade credit to plants for raw material procurement. Furthermore, plants offer trade credit to distribution centers, a novel approach absent from previous studies. The primary objective is to maximize the net present value of shareholders' wealth at the end of the planning horizon, while the secondary objective focuses on maximizing the fill rate. The AEC method and CPLEX solver were employed to solve the model in small dimensions. Given the model's categorization as NP-hard, the nondominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization metaheuristic algorithms were utilized for solving the model in large dimensions. Additionally, the model's validity was investigated through real-world applications. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| Abstract: | Enhancing the management of working capital in supply chains due to fluctuations in demand necessitates the utilization of financial resources such as loans and trade credit. Small and medium-sized enterprises in developing countries often face financial challenges and lack the necessary credit history to secure bank loans. Consequently, trade credit has emerged as a viable debt-based financing alternative. This article presents a two-objective mathematical model for a three-level, multi-period, multi-product supply chain network, in which suppliers provide trade credit to plants for raw material procurement. Furthermore, plants offer trade credit to distribution centers, a novel approach absent from previous studies. The primary objective is to maximize the net present value of shareholders' wealth at the end of the planning horizon, while the secondary objective focuses on maximizing the fill rate. The AEC method and CPLEX solver were employed to solve the model in small dimensions. Given the model's categorization as NP-hard, the nondominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization metaheuristic algorithms were utilized for solving the model in large dimensions. Additionally, the model's validity was investigated through real-world applications. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 1387585X |
| DOI: | 10.1007/s10668-024-05399-3 |
