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Kuo and Lin (2012) introduced an integrated approach of analytic network process (ANP) and data envelopment analysis (DEA) in solving supplier selection problem.
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This paper presents the development of a model based decision support system with a case study on solving the supplier selection problem in a chemical processing industry.
This paper presented a case study on solving the supplier selection problem in the Process industry through a model based decision support system that employs the analytical hierarchy process and grey relational analysis, a multi-criteria methodology aiming towards providing comprehensive support to decision makers in a process industry for supplier selection.
Using this approach, we propose a hierarchical clustering-based method to solve a supplier selection problem and find the proximity of the suppliers.
Lin and Chang (2008) propose mixed-integer programming and fuzzy TOPSIS approach to solve the supplier selection problem.
Chen et al. (2006) presented a fuzzy decision making approach to solve the supplier selection problem.
Chan et al. (2007) developed an AHP based decision making approach to solve the supplier selection problem.
The decision support system relies on an order management model for the logistics management of the enterprise to adequately solve the supplier selection and order allocation problems.
However, as it was mentioned in the introduction, one of the mathematical programming models that is used quite frequently to solve the supplier selection problem is the DEA model.
Cebi and Bayraktar (2005) solved the supplier selection problem for a food processing industry considering the qualitative and quantitative factors by using AHP and lexicographic goal programming (LGP) integrated model.
Chan and Kumar (2007) applied FAHP for solving the global supplier selection problem.
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