Background: Supply chain management is getting more complex and essential with the development of the economy and globalization. Due to several interrelated and integrated logistical components, today's global supply chains are typically nonlinear dynamical systems that may show unpredictable, chaotic, or counterintuitive behaviors. In a volatile business environment, a company must integrate a decision-making strategy to achieve its strategic goals. Digitizing any business can keep up with supply chains that have become increasingly global and complex. Methods: Digital transformation has been rapidly adopted across supply chain networks. A three-echelon supply network has been formulated in discrete time domains for exploring the complex behavior of the dynamical system. The discrete-time models fit more naturally to describe supply chain activities. This paper presents the adaptive management strategy to control the dynamic supply chain systems under uncertainty. The adaptive law is implemented based on the gradient descent method so that it can readily update the control gains of the decision-making strategy. The efficient management strategy helps policymakers implement a decision-support system more precisely and timely. Results: The paper aims to implement the PID controller with adaptation law in the supply chain management's chaotic suppression and synchronization problems under stochastic events. Numerical simulations are presented to evaluate the validity of the proposed algorithms for the operations management of dynamic supply chain networks. The proposed adaptive control strategy provides superior performance and accuracy y over classical control strategies. The decision-making algorithms ensuring business profitability are realized by an adaptive management strategy to cope with market disruptions. Conclusions: Disruptions like customer demand and market conditions impact a multi-echelon supply chain system. A novel adaptive management strategy is presented to regulate uncertain supply chain systems against market disruptions. The control policy effectively utilizes chaos suppression and synchronization schemes to manage complex supply chain networks. The proposed management solutions will help logistics providers prepare for the future and gain a competitive advantage guaranteeing business resilience and sustainability against a volatile market.
The paper discusses the length to beam (L/B) ratio effects on ship resistance at three different Froude numbers using unsteady RANSE simulation. First, the JBC ship model was used as an initial hull form for verification and validation of predicted ship resistance results with measured data, and then the influence of the L/B ratio on ship resistance was carried out. Ship hull forms with different L/B ratios were produced from the initial one by using the Lackenby method. The numerical results obtained show the L/B ratio’s effect on ship resistance. Increases of the L/B ratio led to gradual reduction of the total ship resistance and vice versa. Analysis of the changing of the resistance components indicates that the pressure resistance changes are considerably larger than the frictional one. Finally, the paper analyses the difference in the flow field around the hull of the ship with variation of the L/B ratio to fully understand the physical phenomenon in the change of ship resistance at different L/B parameters.
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