Sustainability and Robust Decision-Support Strategy for Multi-Echelon Supply Chain System Against Disruptions

Long, Le Ngoc Bao; Cuong, Truong Ngoc; Kim, Hwan–Seong; You, Sam–Sang

doi:10.2139/ssrn.4020779

Cited by 3 publications

(5 citation statements)

References 27 publications

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“…A four-echelon supply chain network is considered [5][6]. The diagram of the supply chain network and of inventory control under time-delays is given in Fig.…”

Section: State-space Model Of the Supply Chain Networkmentioning

confidence: 99%

“…There is forward flow of materials and products and backwards flaw of information and orders [3][4]. A general form of a supply chain network consists of four echelons, associated with customers' demand and inventory levels at the side of the retailers, the distributors and the manufacturer [5][6]. The efficiency of a supply chain depends on the maintenance of targeted inventory levels at its individual stages [7][8] .…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear optimal control for supply chain networks under time-delays

Rigatos,

Siani,

Al-Numay

et al. 2024

Preprint

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The article proposes a nonlinear optimal control method for treating the control and stabilization problem of supply chain networks and inventories under time-delays. The state-space model of the supply chain network is considered to have as state variables the customer's demand and the inventories of the manufacturer, of the retailers and of the distributors. The control inputs of the model are the manufacturer's production and the retailer's ordering quantities. The model is subject to time-delays. It is proven that the dynamic model of the supply chain is differentially flat. This model undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method. The linearization relies on Taylor series expansion and on the associated Jacobian matrices. For the linearized state-space model of the supply chain a stabilizing optimal (H-infinity) feedback controller is designed. This controller stands for the solution to the nonlinear optimal control problem under model uncertainty and external perturbations. To compute the controller's feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The method achieves fast and accurate tracking of the targeted setpoints by the state variables of the supply chain system under moderate variations of the control inputs.

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“…A four-echelon supply chain network is considered [5][6]. The diagram of the supply chain network and of inventory control under time-delays is given in Fig.…”

Section: State-space Model Of the Supply Chain Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nonlinear optimal control for supply chain networks under time-delays

Rigatos,

Siani,

Al-Numay

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…In contrast to conventional RNN, only the readout weight is trained; input weight ( in W ), feedback weight ( fb W ), and adjacency matrix ( res W ) are fixed and chosen randomly. In some simple applications where feedback response is not required, fb W can be omitted [21]. Based on similar effects on reservoirs, in W , and fb W are primarily constructed similarly.…”

Section: Prediction Of Chaotic Roll Motions Using Rcmentioning

confidence: 99%

“…If a trajectory in the phase plane intersects itself repeatedly, then a strange attractor and fractals may be observed in the chaotic roll dynamics [39]. , where σ means a hyper-parameter to adjust the performance [21]. The main parameter for prediction via RC is listed in Table 2.…”

Section: Dynamical Analysis Of Chaotic Roll Motionsmentioning

confidence: 99%

Ship Roll Prediction and Parameter Identification under Unknown Ocean Disturbances

Lee,

Kim,

Long

et al. 2023

Preprint

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This paper investigates the roll parameter estimation of periodic disturbances where the amplitude, frequency, offset, and phase are hardly recognized in real practice. The key problem is to make an estimation that could eliminate the unknown disturbance parameters. An adaptive mechanism applies these four parameters to the globally exponential convergence using linear second-order filters and parameter estimation errors. Then, a backstepping controller is employed to make an exponential convergence to zero of the state variables. Moreover, reservoir computing is used to forecast chaotic roll motions to support predictability using Lyapunov exponents and the Poincaré map. Numerical simulations are demonstrated to validate the dynamical behaviors and efficacy of the proposed control scheme with machine learning.

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“…The disruptions in production and the fact that it came to a standstill caused a decrease in the rate of meeting the demand (Panwar et al ., 2022). The disruption of demand, which should be considered in the planning stage of the SC, also affects the remaining steps of the SC with the bullwhip effect (Long et al ., 2022).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

A proposed circular-SCOR model for supply chain performance measurement in manufacturing industry during COVID-19

Özbiltekin-Pala

Koçak

Kazançoğlu

2022

IJQRM

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PurposeCOVID-19 is a global event affecting supply chain operations and human health. With COVID-19, many issues in business models, business processes and supply chains, especially in the manufacturing industry, have had to change. The ability to analyze supply chain performances and ensure circularity in supply chains has become one of the factors whose importance has increased rapidly with COVID-19. Therefore, it aims to determine which supply chain performance criteria come to the fore for the company under consideration to accelerate the transformation into high performance and circularity in supply chains.Design/methodology/approachIn this study, a new circular-SCOR model is proposed, and 17 supply chain performance measurement criteria are prioritized for a manufacturing company in the context of circular economy principles during COVID-19 by using stepwise weight assessment ratio analysis and analytical hierarchy process method, separately.FindingsAs a result, for both methods, in the case study discussed, the demand fulfillment rate is determined as the most prominent criterion in line with the circular economy principles in the COVID-19 period in manufacturing supply chains.Originality/valueIt is expected that this study will contribute to managers and policy makers as it addresses the “new normal” that started after COVID-19 and the criteria to be considered in supply chain performance measurement and emphasizes the need to adopt circular supply chains, especially in manufacturing industries.

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Sustainability and Robust Decision-Support Strategy for Multi-Echelon Supply Chain System Against Disruptions

Cited by 3 publications

References 27 publications

Nonlinear optimal control for supply chain networks under time-delays

Nonlinear optimal control for supply chain networks under time-delays

Ship Roll Prediction and Parameter Identification under Unknown Ocean Disturbances

A proposed circular-SCOR model for supply chain performance measurement in manufacturing industry during COVID-19

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