A fuzzy inference system for supply chain risk management

Hülya Behret; Başar Öztayşi; Cengiz Kahraman

doi:10.1007/978-3-642-25658-5_52

A fuzzy inference system for supply chain risk management

Hülya Behret^*
, Başar Öztayşi
, Cengiz Kahraman

^*Corresponding author for this work

Department of Industrial Engineering

Erciyes University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

37 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 language	English
Title of host publication	Practical Applications of Intelligent Systems
Subtitle of host publication	Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering, Shanghai, China, Dec 2011 (ISKE2011)
Editors	Yinglin Wang, Tianrui Li
Pages	429-438
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-642-25658-5_52
Publication status	Published - 2011

Publication series

Name	Advances in Intelligent and Soft Computing
Volume	124
ISSN (Print)	1867-5662

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Fuzzy Inference Systems
Fuzzy Sets
Risk Management
Supply Chain

Access to Document

10.1007/978-3-642-25658-5_52

Cite this

Behret, H., Öztayşi, B., & Kahraman, C. (2011). A fuzzy inference system for supply chain risk management. In Y. Wang, & T. Li (Eds.), Practical Applications of Intelligent Systems: Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering, Shanghai, China, Dec 2011 (ISKE2011) (pp. 429-438). (Advances in Intelligent and Soft Computing; Vol. 124). https://doi.org/10.1007/978-3-642-25658-5_52

Behret, Hülya ; Öztayşi, Başar ; Kahraman, Cengiz. / A fuzzy inference system for supply chain risk management. Practical Applications of Intelligent Systems: Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering, Shanghai, China, Dec 2011 (ISKE2011). editor / Yinglin Wang ; Tianrui Li. 2011. pp. 429-438 (Advances in Intelligent and Soft Computing).

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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",

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doi = "10.1007/978-3-642-25658-5\_52",

language = "English",

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Behret, H, Öztayşi, B & Kahraman, C 2011, A fuzzy inference system for supply chain risk management. in Y Wang & T Li (eds), Practical Applications of Intelligent Systems: Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering, Shanghai, China, Dec 2011 (ISKE2011). Advances in Intelligent and Soft Computing, vol. 124, pp. 429-438. https://doi.org/10.1007/978-3-642-25658-5_52

A fuzzy inference system for supply chain risk management. / Behret, Hülya; Öztayşi, Başar ; Kahraman, Cengiz.
Practical Applications of Intelligent Systems: Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering, Shanghai, China, Dec 2011 (ISKE2011). ed. / Yinglin Wang; Tianrui Li. 2011. p. 429-438 (Advances in Intelligent and Soft Computing; Vol. 124).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A fuzzy inference system for supply chain risk management

AU - Behret, Hülya

AU - Öztayşi, Başar

AU - Kahraman, Cengiz

PY - 2011

Y1 - 2011

N2 - 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).

AB - 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).

KW - Fuzzy Inference Systems

KW - Fuzzy Sets

KW - Risk Management

KW - Supply Chain

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DO - 10.1007/978-3-642-25658-5_52

M3 - Conference contribution

AN - SCOPUS:84855214634

SN - 9783642256578

T3 - Advances in Intelligent and Soft Computing

SP - 429

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BT - Practical Applications of Intelligent Systems

A2 - Wang, Yinglin

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ER -

Behret H, Öztayşi B , Kahraman C. A fuzzy inference system for supply chain risk management. In Wang Y, Li T, editors, Practical Applications of Intelligent Systems: Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering, Shanghai, China, Dec 2011 (ISKE2011). 2011. p. 429-438. (Advances in Intelligent and Soft Computing). doi: 10.1007/978-3-642-25658-5_52

A fuzzy inference system for supply chain risk management

Abstract

Publication series

UN SDGs

Keywords

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