@inproceedings{1613c7aaa2104f86b5af5d6654b2de58,
title = "A fuzzy inference system for supply chain risk management",
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).",
keywords = "Fuzzy Inference Systems, Fuzzy Sets, Risk Management, Supply Chain",
author = "H{\"u}lya Behret and Ba{\c s}ar {\"O}ztay{\c s}i and Cengiz Kahraman",
year = "2011",
doi = "10.1007/978-3-642-25658-5_52",
language = "English",
isbn = "9783642256578",
series = "Advances in Intelligent and Soft Computing",
pages = "429--438",
editor = "Yinglin Wang and Tianrui Li",
booktitle = "Practical Applications of Intelligent Systems",
}