A fuzzy model for supplier selection in quantity discount environments

Traditionally, supplier selection should simultaneously take into account numerous heterogeneous criteria, and then is a tedious task for the purchasing decision makers. It becomes especially complicated when quantity discounts are considered at the same time. Under such manner, most studies often f...

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Bibliographic Details
Published in:Expert systems with applications Vol. 36; no. 10; pp. 12179 - 12187
Main Authors: Wang, Tai-Yue, Yang, Yih-Hwang
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.12.2009
Subjects:
Analytical Hierarchy Process
Fuzzy compromise programming
Multi-Objective Linear Programming
Supplier selection
Supplier selection
Multi-Objective Linear Programming
Analytical Hierarchy Process
Fuzzy compromise programming
ISSN:0957-4174, 1873-6793
Online Access:Get full text
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Summary:Traditionally, supplier selection should simultaneously take into account numerous heterogeneous criteria, and then is a tedious task for the purchasing decision makers. It becomes especially complicated when quantity discounts are considered at the same time. Under such manner, most studies often formulate such a problem as a Multi-Objective Linear Programming (MOLP) problem, and then scale it down to a Mixed Integer Programming (MIP) problem to handle the inherited multi-objectives simultaneously. However, this approach often neglects to consider scaling and subjective weighting issues. In order to ease the problem mentioned above and to obtain a more reasonable compromise solution for allocating order quantities among suppliers with their quantity discount rate offered, the Analytical Hierarchy Process (AHP) and fuzzy compromise programming are introduced in this study. An illustrated example is presented to demonstrate the proposed model and to illuminate two kinds of attitudes for decision makers. The information from the experiments can be utilized further to explain the suppliers’ possible improvement and to help create win–win policies.
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ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2009.03.018