Title: A cluster collaborative synchronisation dynamic model of the dissipative coupling supply chain network

Authors: Bing Yang; Gang Zhao; Ming-hua Hu; Chang-ping Liu; Ying-bao Yang

Addresses: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China ' Civil Aviation Management Institute of China, Beijing 100102, China ' College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China ' Faculty of Management Engineering, Huaiyin Institute of Technology, Huaiyin 223001, China ' College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Abstract: The supply chain network is regarded as a dynamic system consisting of member companies with dynamic behaviours. In this paper an attempt is made to describe the dynamic behaviours of each member company with an autonomous dynamic system to establish the cluster collaborative synchronisation dynamic model for dissipative coupling supply chain networks. Considering the materials flow, transaction amount and substitutability among the member companies of the supply chain network, a collaborative closeness matrix of the supply chain network was set. Based on the proposed model, the cluster collaborative synchronisation interval of the supply chain network was calculated and the simulation results were obtained. This model is not proved to be suitable for the general scale supply networks, but also suitable for the large-scale complex supply chain networks. Based on the proposed model and the cluster collaborative synchronisation interval, we can optimise strategy for the collaborative synchronisation operation among the member companies of the supply chain network.

Keywords: dynamic model; supply chain network; synchronisation interval; cluster collaboration; dissipative coupling.

DOI: 10.1504/IJSN.2020.111132

International Journal of Security and Networks, 2020 Vol.15 No.4, pp.214 - 223

Received: 30 Dec 2019
Accepted: 06 Jan 2020

Published online: 26 Oct 2020 *

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