NDLI: Supplier selection for managing supply risks in supply chain: a fuzzy approach

Content Provider	Springer Nature Link
Author	Paul, Sanjoy Kumar
Copyright Year	2015
Abstract	Supplier selection is one of the most important tasks for supply chain decision making, and there are many quantitative and qualitative factors that affect this process. This paper develops a simple and user-friendly supplier selection process for a supply chain which considers various selection criteria for managing supply risks. A rule-based fuzzy inference system (FIS) model is developed using the fuzzy logic toolbox in MATLAB R2012a to select the most excellent supplier by considering both quantitative and qualitative selection criteria. We identify a total of 18 selection criteria, of which four are quantitative and 14 qualitative. Risk factors are also incorporated in the model by developing fuzzy input and output criteria, and the best supplier is selected based on the aggregated supplier ranking index value. Finally, a numerical example presented to explain the usefulness of the developed model.
Starting Page	657
Ending Page	664
Page Count	8
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	79
Issue Number	1-4
e-ISSN	14333015
Language	English
Publisher	Springer London
Publisher Date	2015-02-13
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Supplier selection Supply chain Risk management Fuzzy logic Fuzzy inference system Industrial and Production Engineering Production Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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