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Article type: Research Article
Authors: Liu, Peidea; * | Hendalianpour, Ayadb
Affiliations: [a] School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan, Shandong, China | [b] Soshianest Enterprise Miner, North Vancouver, BC V7N2J7, Canada
Correspondence: [*] Corresponding author. Peide Liu, School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan, Shandong, China. E-mail: peide.liu@gmail.com.
Abstract: Financial flows are one of the three majors in a Supply Chain (SC). Ignoring financial flows, regardless of the quality of freight transport and information, could lead the organization to a state of bankruptcy, which is a situation directly resulting from a lack of control over financial inputs/outputs. This study proposes a multi-product mathematical model, which makes it possible to choose among suppliers, manufacturing sites, distribution centres, retailers, and transportation vehicles. The purpose of the model is to integrate physical and material dimensions to maximize net corporate profits through inbound and outbound financial flows; it involves payment mechanisms between the financial and physical flows through maximizing the cash flows of manufacturing sites and suppliers, as two conflicting objectives that must consider the reciprocal effects of their decisions. These objectives are calculated by subtracting costs from the revenue; this process, of course, will ultimately result in an optimization of the organization’s financial flow. To solve the proposed mathematical model, the study relies on two algorithms, namely Particle Swarm Optimization (PSO) and Imperialist Competition Algorithm (ICA). The sample under investigation is solved separately using the three algorithms, and results are then compared. The observations of the study reveal the better performance of PSO.
Keywords: Supply chain financial flow, inbound and outbound flow, mathematical modeling, particle swarm optimization, imperialist competitive algorithm
DOI: 10.3233/JIFS-201068
Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 2561-2579, 2021
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