A fuzzy inference system for supply chain risk management

Hülya Behret*, Başar Öztayşi, Cengiz Kahraman

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

31 Citations (Scopus)

Abstract

Risk management is the identification, assessment, and prioritization of risks followed by coordinated and economical application of resources to minimize, monitor, and control the probability and/or impact of unfortunate events. In the last decade risk management has become a vital part of supply chain management. The risk sources of supply chain are identified in five areas namely: transport/distribution, manufacturing, order cycle, warehousing, and procurement. The aim of the study is to build a supply chain risk measurement system using Fuzzy Inference Systems (FIS).

Original languageEnglish
Title of host publicationPractical Applications of Intelligent Systems
Subtitle of host publicationProceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering, Shanghai, China, Dec 2011 (ISKE2011)
EditorsYinglin Wang, Tianrui Li
Pages429-438
Number of pages10
DOIs
Publication statusPublished - 2011

Publication series

NameAdvances in Intelligent and Soft Computing
Volume124
ISSN (Print)1867-5662

Keywords

  • Fuzzy Inference Systems
  • Fuzzy Sets
  • Risk Management
  • Supply Chain

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