A Convex Dynamic Approach for Globally Optimal Profit in Supply Chains

Mojtaba Azizian, Mohammad Mehdi Sepehri and Mohammad Ali Rastegar
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Mojtaba Azizian: Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran 1411713116, Iran
Mohammad Mehdi Sepehri: Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran 1411713116, Iran
Mohammad Ali Rastegar: Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran 1411713116, Iran

Mathematics, 2022, vol. 10, issue 3, 1-19

Abstract: Supply chain finance aims to coordinate multiple stakeholders to maximize the flow of cash and internal and external funding along the supply chain, as shown in prior research. From a regulatory standpoint, the goal of this paper is to maximize the profitability of an entire supply chain. As a result, a constrained finite time Linear Quadratic Regulation (LQR) approach is provided for determining an entity’s optimal profit state in a supply chain. The framework is represented by discrete-time linear dynamical equations for each entity in the supply chain network, taking state and input variables into account. The problem is formulated in terms of a convex quadratic programming optimization for which several numerically efficient algorithms are readily available. In order to validate the approach, it was tested on two topologies. The first topology is a fully connected supply chain with six nodes; the second is a simple topology based on the Iranian pharmaceutical supply chain. The results indicate that the proposed approach successfully planned production and financing decisions within the simulated supply chain and obtained globally optimal profit for all supply chain stakeholders.

Keywords: financial supply chain management; simulation; optimization; optimal control; linear quadratic regulation; linear dynamical equations (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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