A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming

A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming

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Article ID: iaor19992938
Country: Netherlands
Volume: 56/57
Issue: 1
Start Page Number: 199
End Page Number: 212
Publication Date: Sep 1998
Journal: International Journal of Production Economics
Authors: ,
Keywords: decision theory: multiple criteria, artificial intelligence: decision support, programming: linear, analytic hierarchy process
Abstract:

Supplier selection is a multicriteria problem which includes both qualitative and quantitative factors. In order to select the best suppliers it is necessary to make a trade off between these tangible and intangible factors some of which may conflict. When capacity constraints exist, this problem becomes more complicated as, in these circumstances, managers should decide about two problems: which suppliers are the best and how much should be purchased from each selected supplier. Some authors have applied mixed integer, goal and multi-objective programming to solve this problem. As these techniques are mathematical, they have significant problems in considering qualitative factors which are very important in supplier selection, especially when supplier partnership is desired. In this article an integration of analytical hierarchy process and linear programming is proposed to consider both tangible and intangible factors in choosing the best suppliers and placing the optimum order quantities among them such that the total value of purchasing becomes maximum. This model can be applied to supplier selection with and without capacity constraints. A numerical example is presented and the model advantages are discussed.

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