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Business continuity-inspired resilient supply chain network design

Namdar, Jafar ; Torabi, S. Ali ; Sahebjamnia, Navid ; Nilkanth Pradhan, Ninad

International journal of production research, 2021-03, Vol.59 (5), p.1331-1367 [Periódico revisado por pares]

London: Taylor & Francis

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  • Título:
    Business continuity-inspired resilient supply chain network design
  • Autor: Namdar, Jafar ; Torabi, S. Ali ; Sahebjamnia, Navid ; Nilkanth Pradhan, Ninad
  • Assuntos: Attitudes ; Business ; business continuity management ; Decision making ; Disruption ; Mathematical models ; Multiple criterion ; Network design ; possibilistic programming ; Resilience ; Resilience management ; Strategic planning ; supply chain design ; Supply chains ; two-stage stochastic programming
  • É parte de: International journal of production research, 2021-03, Vol.59 (5), p.1331-1367
  • Descrição: Supply chains are prone to several operational and disruption risks. In order to design a resilient supply chain network capable of responding to such potential risks suitably, this paper proposes a novel framework for the business continuity-inspired resilient supply chain network design (BCRSCND) problem, which includes three steps. First, four resilience dimensions including Anticipation, Preparation, Robustness, and Recovery are considered to quantify the resilience score of each facility using a multi-criteria decision-making technique and considering a comprehensive set of resilience strategies. In the second step, the critical processes and their business continuity metrics (which are vital for supply chain continuity), are identified. The outputs of the first two steps provide the inputs of a novel two-stage mixed possibilistic-stochastic programing (TSMPSP) model. The model aims to design a multi-echelon, multi-product resilient supply chain network under both operational and disruption risks. The proposed TSMPSP model allows decision makers to incorporate their risk attitudes into the design process. After converting the original TSMPSP model into the crisp counterpart, several sensitivity analyses are conducted on different features of hypothetical disruptions (i.e. their severity, likelihood and location) and DM's risk attitudes from which useful managerial insights are provided.
  • Editor: London: Taylor & Francis
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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