Int. J. of Industrial and Systems Engineering   »   2014 Vol.18, No.3

 

 

Title: A supply chain disturbance management fuzzy decision support system

 

Authors: Isabel L. Nunes; V. Cruz-Machado

 

Addresses:
Faculdade de Ciências e Tecnologia, Departamento Engenharia Mecânica e Industrial, Universidade Nova de Lisboa, Campus de Caparica, 2829-516 Caparica, Portugal; Unidade de Investigação em Engenharia Mecânica e Industrial (UNIDEMI), FCT/UNL, Campus de Caparica, 2829-516 Caparica, Portugal
Faculdade de Ciências e Tecnologia, Departamento Engenharia Mecânica e Industrial, Universidade Nova de Lisboa, Campus de Caparica, 2829-516 Caparica, Portugal; Unidade de Investigação em Engenharia Mecânica e Industrial (UNIDEMI), FCT/UNL, Campus de Caparica, 2829-516 Caparica, Portugal

 

Abstract: This paper presents a supply chain disturbance management fuzzy decision support system model developed to support managers in their decision-making process of selecting the best operational policy (e.g., mitigation and/or contingency plans) to counter supply chain disturbances, thus improving supply chain resilience. The selection of such operational policies is based on the calculation of performance indexes that reflect the supply chain performance in different scenarios (e.g., normal operation, affected by disturbances, implementation of mitigation plans or implementation of contingency plans). The developed system lays on two pillars: first, on the use of fuzzy set theory to model the uncertainty associated with disturbances, their effects on the supply chain and the computation of the referred performance indexes; second, on the simulation of the supply chain under the effect of disturbances or operational policies, by coupling the system with a simulation software.

 

Keywords: supply chain management; SCM; disturbance management; fuzzy DSS; decision support systems; supply chain disturbances; fuzzy set theory; FST; supply chain resilience; performance indexes; supply chain performance; fuzzy logic; uncertainty modelling; simulation; supply chain disruption.

 

DOI: 10.1504/IJISE.2014.065536

 

Int. J. of Industrial and Systems Engineering, 2014 Vol.18, No.3, pp.306 - 334

 

Available online: 29 Oct 2014

 

 

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