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  • Economics  (2)
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  • Economics  (2)
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  • 1
    In: RAIRO - Operations Research, EDP Sciences, Vol. 57, No. 2 ( 2023-03), p. 787-815
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0399-0559 , 2804-7303
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 1468388-X
    SSG: 3,2
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    EDP Sciences ; 2023
    In:  RAIRO - Operations Research
    In: RAIRO - Operations Research, EDP Sciences
    Abstract: Nonlinear system dynamics and feedback control theory are presented for management optimization of supply chain system. Linearization and simplification method are widely used in analyzing system dynamics of supply chains because actual production models are highly complex and nonlinear systems. With the advanced system dynamics, it is possible directly to deal with nonlinear dynamical problems without linear approximate methods so that the decision makers can obtain more accurate results for systematic management strategies. This paper aims to propose nonlinear system theory to explore dynamical behavior and control synthesis of production-distribution system by utilizing Forrester’s model. A novel super twisting sliding mode control (SWT-SMC) algorithm has been presented based on adaptation law, ensuring management optimization against disruptions. The closed-loop system stability has been guaranteed by using Lyapunov theory. Extensive numerical simulations have been conducted to validate the efficacy and reliability of the adaptive super twisting sliding mode control (ASWT-SMC) algorithm. Four types of decision criteria have been employed to compare system performance between control strategies. With superb decision scheme powered by control algorithm, novel supply chain software can learn an ever-fluctuating production flow and anticipate the need for changes in real market.
    Type of Medium: Online Resource
    ISSN: 0399-0559 , 2804-7303
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 1468388-X
    SSG: 3,2
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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