Abstract
This study is concerned with dynamical investigation, electrical circuit realization, and emulation of a fractional three-echelon supply chain system. In the financial realm, long-term memory effects play important roles. On the other hand, most financial systems are uncertain with unknown nonlinear dynamics. However, most studies on nonlinear supply chains neither consider the fractional calculus nor take advantage of state-of-the-art emulation methods. These issues motivated the current study. A fractional-order chaotic three-echelon supply chain system is studied. At first, the system’s dynamic is studied through Lyapunov exponent and bifurcation diagrams. It is shown that a slight deferent in some parameters of the system can dramatically change the behavior of the system. Then, a real-time analog circuit is designed and implemented to investigate the system’s chaotic behavior. This way, the system’s chaotic attractors are empirically demonstrated. Finally, emulation and interpolation of the fractional-order chaotic system using the Gaussian process have been studied, and its luminous results have been presented.
Highlights
Chains are nonlinear dynamical systems triggered by various uncertain factors such as customer demands [1,2,3,4,5,6]
In the last part of the current study, we have investigated the application of Gaussian process (GP) to a three-echelon supply chain system
Lyapunov exponent and bifurcation diagrams, the presence of chaos within the system was verified, and was is demonstrated that a slight deferent in some system parameters can considerably change the behavior of the system
Summary
Chains are nonlinear dynamical systems triggered by various uncertain factors such as customer demands [1,2,3,4,5,6]. The success of supply chains depends on various factors, including transportation fleets, machinery, and equipment, the effectiveness of such systems is primarily determined by the quality of management decisions [13,14,15]. Uncertainties in such systems make their control and management demanding tasks [16,17,18]
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