Management and optimisation of chaotic supply chain system using adaptive sliding mode control algorithm

Xu, Xiao; Lee, Sang‐Do; Kim, Hwan–Seong; You, Sam–Sang

doi:10.1080/00207543.2020.1735662

Cited by 37 publications

(19 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lin and Naim [22] developed a hybrid ATO system dynamics model based on the well-established inventory and order based production control systems and analytically studied the impact of nonlinearities on its dynamic performance. Xu and Lee [23] presented A multiechelon supply chain system having parametric perturbations and disturbances to demonstrate chaotic nonlinear dynamical behaviors.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation and Analysis of the Complex Dynamic Behavior of Supply Chain Inventory System from Different Decision Perspectives

Zhang

Wang²,

Yang

et al. 2020

Complexity

View full text Add to dashboard Cite

Based on the local decision perspective and the global decision perspective, considering the limitation of supply capacity and prohibiting returns, the system dynamics method is used to establish a nonlinear supply chain system model. We use the Z-transform theory to transform the dynamic transfer equation into a block diagram, build a supply chain system simulation model, and use it to conduct simulation experiments. The Wolf reconstruction method is used to calculate the largest Lyapunov exponent (LLE) value of each node or combined system to judge the stability of the system. Based on different decision-making perspectives, under different combinations of safety stock factors and demand scenarios, the adjustment coefficients’ decision-making schemes that keep each node in a stable state are obtained. Then, we comparatively analyze the inventory changes of each node and combined system in a stable state under different decision-making schemes.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Simulation and Analysis of the Complex Dynamic Behavior of Supply Chain Inventory System from Different Decision Perspectives

Zhang

Wang²,

Yang

et al. 2020

Complexity

View full text Add to dashboard Cite

show abstract

“…To tackle such uncertainties, many studies select different modeling methods given the presence or absence of historical data (Ivanov and Dolgui 2020;Zhang et al 2021). However, Turken et al (2020) argue that the various sources of uncertainties is a serious issue, which significantly reduces the flexibility of decisions, and there are only few studies selecting modeling methods with a consideration of the complexity of uncertainty sources (Costa et al 2020;Xu et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Sustainable closed-loop supply chain network under uncertainty: a response to the COVID-19 pandemic

Rafigh

Akbari

Bidhandi

et al. 2021

Environ Sci Pollut Res

View full text Add to dashboard Cite

This study proposes a sustainable closed-loop supply chain under uncertainty to create a response to the COVID-19 pandemic. In this paper, a novel stochastic optimization model integrating strategic and tactical decision-making is presented for the sustainable closed-loop supply chain network design problem. This paper for the first time implements the concept of sustainable closed-loop supply chain for the application of ventilators using a stochastic optimization model. To make the problem more realistic, most of the parameters are considered to be uncertain along with the normal probability distribution. Since the proposed model is more complex than majority of previous studies, a hybrid whale optimization algorithm as an enhanced metaheuristic is proposed to solve the proposed model. The efficiency of the proposed model is tested in an Iranian medical ventilator production and distribution network in the case of the COVID-19 pandemic. The results confirm the performance of the proposed algorithm in comparison with two other similar algorithms based on different multi-objective criteria. To show the impact of sustainability dimensions and COVID-19 pandemic for our proposed model, some sensitivity analyses are done. Generally, the findings confirm the performance of the proposed sustainable closed-loop supply chain for the pandemic cases like COVID-19. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-021-16077-6.

show abstract

“…This Sustainability 2021, 13, 9407 2 of 13 makes the assessment of a closed-loop supply chains for the ventilators important. Such a tendency motivates this effort to develop a stochastic optimization model for the case of ventilator logistics network design [39][40][41][42][43][44][45].…”

Section: Introductionmentioning

confidence: 99%

“…To tackle such uncertainties, many studies select different modeling methods given the presence or absence of historical data [19,46]. However, Turken et al [40] argues that the various sources of uncertainties are a serious issue, which significantly reduces flexibility of decisions, and there are only few studies selecting modeling methods with a consideration of the complexity of uncertainty sources [5,44].…”

Section: Introductionmentioning

confidence: 99%

Green Closed-Loop Supply Chain Network under the COVID-19 Pandemic

2021

View full text Add to dashboard Cite

The closed-loop supply chain considers conceptually the possibility of reverse logistics with the use of recycling, remanufacturing and disposal centers. This study contributes for the first time a green closed-loop supply chain framework for the ventilators, which are highly important in the case of the COVID-19 pandemic. The proposed model simulates a case study of Iranian medical ventilator production. The proposed model includes environmental sustainability to limit the carbon emissions as a constraint. A novel stochastic optimization model with strategic and tactical decision making is presented for this closed-loop supply chain network design problem. To make the proposed ventilator logistics network design more realistic, most of the parameters are considered to be uncertain, along with the normal probability distribution. Finally, to show the managerial dimensions under the COVID-19 pandemic for our proposed model, some sensitivity analyses are performed. Results confirm the high impact of carbon emissions and demand variations on the optimal solution in the case of COVID-19.

show abstract

Management and optimisation of chaotic supply chain system using adaptive sliding mode control algorithm

Cited by 37 publications

References 24 publications

Simulation and Analysis of the Complex Dynamic Behavior of Supply Chain Inventory System from Different Decision Perspectives

Simulation and Analysis of the Complex Dynamic Behavior of Supply Chain Inventory System from Different Decision Perspectives

Sustainable closed-loop supply chain network under uncertainty: a response to the COVID-19 pandemic

Green Closed-Loop Supply Chain Network under the COVID-19 Pandemic

Contact Info

Product

Resources

About