Integration of Liability Payment and New Funding Entries in the Optimal Design of a Supply Chain Network

محورهای موضوعی : Financial Engineering

Abbas Biglar ¹ (Department of Industrial Engineering, North Tehran branch, Islamic Azad University, Tehran, Iran)
Nima Hamta ² (Department of Mechanical Engineering, Arak University of Technology, Arak, Iran)
Mona Ahmadi Rad ³ (Department of Industrial Engineering, North Tehran branch, Islamic Azad University, Tehran, Iran)

تاریخ دریافت : 1400/03/21 تاریخ پذیرش : 1400/07/08 تاریخ انتشار : 1401/04/10

کلید واژه: Supply chain network design, Economic Value Added, Mathematical Programming, Supply chain optimization,

چکیده مقاله :

In recent years, the supply chain network design (SCND) problems that integrate financial issues have attracted the attention of managers and researchers. In this paper, in order to address an SCND problem, a mixed-integer nonlinear programming (MINLP) model developed that considers operational and financial decisions simultaneously for designing a deterministic multi-echelon, multi-product, and multi-period supply chain network. The developed model provides the possibility of opening or closing facilities at every time period to adapt to market fluctuations. The model also considers bank loans, liability repayment, and new capital from shareholders as decision variables, therefore, it provides an accounts payable policy for the company managers. In addition to common operational objectives(profit/cost) and constraints, we also applied the economic value added (EVA) index to measure the financial performance of supply chain and lower and/or upper limit value for financial ratios to ensure the company's financial health, while making decisions at strategic and tactical levels. To show the model applicability, data of a case study in the literature employed and solved using BARON solver in GAMS software. The results clearly show an improvement in the total value created for the company compared to the base model, so it can be applied as an effective decision tool.

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