A Fuzzy Based Decision Support System For Supply Chain Disruption Management

Authors

  • Amir Daneshvar Department of Industrial Management, Electronic Branch Islamic Azad University, Tehran, Iran
  • Behnam Barzegar Department of Computer Engineering, Nowshahr Branch, Islamic Azad University, Nowshahr, Iran
  • Fariba Salahi Department of Industrial Management, Electronic Branch Islamic Azad University, Tehran, Iran
Abstract:

Among the supply chain risk types, disruptions that result from natural disasters, sanctions, transportation problems and equipment failure can seriously disrupt or delay the flow of material, information and cash. The aim of this research was to propose a hybrid model for disruption management, which is the process of achieving plans or strategies to reduce the expenses incurred by the disruption. For this purpose; first, we identified disruptions and mitigation strategies by using the nominal group technique. Then, the interaction between disruptions was formulated by the fuzzy DEMATEL technique. Consequently, with regard to the uncertainty of data, fuzzy logic was used for modeling the uncertainty of disruptions. Finally, mitigating strategies were selected and ranked with PROMETHEEΙΙ. Considering the existence of 4 types of responses of chain against risks, which include: 1- risk control and endurance 2-risk flexibility 3- risk avoidance 4- risk transfer and assignment; results show that according to the type of disorder, the risk management strategy changes and in general (taking into account the causal relationship between disorders), the risk transfer strategy it was more suitable

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

A fuzzy logic based decision support system for evaluation of suppliers in supply chain management practices

Supply chainmanagement is an increasingly important organizational concern, and proper evaluation of suppliers constitutes one essential element of supply chain success. Continuous evaluation of a particular supplier becomesmore important considering the fact that in most industries the cost of raw materials and component parts constitutes the main cost of a product, such that in some cases it ...

full text

A multi-agent decision support system for supply chain management

Supply Chain Management (SCM) involves a number of activities from negotiating with suppliers to competing for customer orders and scheduling the manufacturing process and delivery of goods. The activities are different in their nature: they work with various data, have different tasks and constraints. At the same time, they are interrelated to ensure the achievement of the ultimate goal of max...

full text

Multi-Agent Decision Support System for Supply Chain Management

This paper presents an extended abstract of the author’s doctoral research project on developing a multi-agent intelligent system for automatic managing supply chains. Supply chain management (SCM) is a very complex and dynamic environment. The doctoral work, which started in October 2005, is dedicated to finding better solutions for successful performance in the domain of real-time SCM.

full text

Decision Support Technique for Supply Chain Management

In this paper, we propose a method for supporting decision makers in the domain of supply chain management. Our objective is the global optimization instead of optimizing independent subsystems of the supply chain. The method architecture is based on combination of the simulation and optimization techniques which includes a multi-objectives optimization module and a simulation module. The optim...

full text

A Simulation-based Bpr Support System for Supply Chain Management

Modern manufacturing enterprises must collaborate with a large number of suppliers to design and produce their products. Management of these supply chains is crucial. This paper proposes a simulation-based, supply chain management system, which supports the implementation of BPR in an integrated system environment. The scope of the BPR includes management processes for production and operations...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 11  issue 2

pages  1- 10

publication date 2020-05-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023