Volume 57, Number 2, March-April 2023
|Page(s)||787 - 815|
|Published online||28 April 2023|
Decision support system for managing multi-echelon supply chain networks against disruptions using adaptive fractional order control algorithm
Division of Logistics, Korea Maritime and Ocean University, Busan, Republic of Korea
2 Division of Mechanical Engineering, Korea Maritime and Ocean University, Busan, Republic of Korea
* Corresponding author: firstname.lastname@example.org
Accepted: 22 March 2023
Managing highly evolving supply chains can be challenging, especially when vulnerable to disruptions and risks. This paper deals with a supply chain system’s dynamical analysis and efficient management strategy using a four-stage hyperchaotic Lorenz–Stenflo equation under disruptive events. Nonlinear behaviors are intensely investigated by eigenvalue and bifurcation analysis to identify supply chain risks. Then phase portraits are presented to illustrate the bullwhip effect negatively influencing the performance of various stages of multi-echelon supply chains. Resilient supply chains have been developed along with dynamic identification by realizing an adaptive fractional-order controller. An efficient control algorithm can optimize the management system while reducing potential risks by employing control theory in a decision support system. Performance criteria have been exploited to validate the control methodology. Using digital management algorithms, decision-makers might effectively cope with chaos suppression and synchronization problems, ensuring productivity and sustainability. Finally, the novel decision-making strategy can offer new insights into effectively managing digital supply chain networks against market volatility.
Mathematics Subject Classification: 70K50 / 93B12 / 93B52 / 93C10 / 93C40 / 93C55 / 93D05
Key words: Bullwhip effect / multi-echelon supply chain / disruptions / control theory / chaos suppression and synchronization
© The authors. Published by EDP Sciences, ROADEF, SMAI 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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