Simulation based fuzzy TOPSIS approach for group multi-criteria supplier selection problem

Supplier selection is nowadays one of the critical topics in supply chain management. This paper presents a new decision making approach for group multi-criteria supplier selection problem, which clubs supplier selection process with order allocation for dynamic supply chains to cope market variatio...

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Bibliographic Details
Published in:Engineering applications of artificial intelligence 2012-04, Vol.25 (3), p.507-519
Main Authors: Zouggari, Akram, Benyoucef, Lyes
Format: Article
Language:English
Subjects:
Allocations
Computer Science
Decision making
Fuzzy
Fuzzy logic
Fuzzy set theory
Fuzzy-AHP
Fuzzy-TOPSIS
Knowledge
Operations Research
Order allocation
Simulation
Supplier selection
Suppliers
Supply chains
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Summary:Supplier selection is nowadays one of the critical topics in supply chain management. This paper presents a new decision making approach for group multi-criteria supplier selection problem, which clubs supplier selection process with order allocation for dynamic supply chains to cope market variations. More specifically, the developed approach imitates the knowledge acquisition and manipulation in a manner similar to the decision makers who have gathered considerable knowledge and expertise in procurement domain. Nevertheless, under many conditions, exact data are inadequate to model real-life situation and fuzzy logic can be incorporated to handle the vagueness of the decision makers. As per this concept, fuzzy-AHP method is used first for supplier selection through four classes (CLASS I: Performance strategy, CLASS II: Quality of service, CLASS III: Innovation and CLASS IV: Risk), which are qualitatively meaningful. Thereafter, using simulation based fuzzy TOPSIS technique, the criteria application is quantitatively evaluated for order allocation among the selected suppliers. As a result, the approach generates decision-making knowledge, and thereafter, the developed combination of rules order allocation can easily be interpreted, adopted and at the same time if necessary, modified by decision makers. To demonstrate the applicability of the proposed approach, an illustrative example is presented and the results analyzed.
ISSN:0952-1976
1873-6769
DOI:10.1016/j.engappai.2011.10.012