Abstract
Article history: Received January 12, 2013 Received in revised format 15 April 2013 Accepted 26 April 2013 Available online April 28 2013 This paper presents an integrated supplier selection and inventory management using grey relationship model (GRM) as well as multi-objective decision making process. The proposed model of this paper first ranks different suppliers based on GRM technique and then determines the optimum level of inventory by considering different objectives. To show the implementation of the proposed model, we use some benchmark data presented by Talluri and Baker [Talluri, S., & Baker, R. C. (2002). A multi-phase mathematical programming approach for effective supply chain design. European Journal of Operational Research, 141(3), 544-558.]. The preliminary results indicate that the proposed model of this paper is capable of handling different criteria for supplier selection. © 2013 Growing Science Ltd. All rights reserved.
Highlights
Initial buying decisions such as make-or-buy decisions and supplier selection are considered as the most important strategies for companies
With the widespread use of manufacturing philosophies such as just-in-time (JIT), emphasis had shifted to the concurrent consideration of cardinal and ordinal data in the supplier-selection process. They explained that the application of data envelopment analysis (DEA) for supplier-selection problems rely on total flexibility of the weights
Their work dealt with the development of an integrated supplier selection and multi-echelon distribution inventory model (MEDIM) for the original equipment manufacturing firm in a built-to-order supply chain environment based on fuzzy analytical hierarchy process (FAHP) and a genetic algorithm
Summary
Initial buying decisions such as make-or-buy decisions and supplier selection are considered as the most important strategies for companies. With the widespread use of manufacturing philosophies such as just-in-time (JIT), emphasis had shifted to the concurrent consideration of cardinal and ordinal data in the supplier-selection process They explained that the application of data envelopment analysis (DEA) for supplier-selection problems rely on total flexibility of the weights. Their work dealt with the development of an integrated supplier selection and multi-echelon distribution inventory model (MEDIM) for the original equipment manufacturing firm in a built-to-order supply chain environment based on fuzzy analytical hierarchy process (FAHP) and a genetic algorithm. Wang et al (2004) integrated product characteristics to supply chain strategy and adopted supply chain operations reference (SCOR) model level I performance metrics as the decision criteria They developed an integrated analytic hierarchy process (AHP) and preemptive goal programming (PGP) based multi-criteria decisionmaking methodology to consider both qualitative and quantitative factors in supplier selection. They developed an integrated analytic hierarchy process (AHP) and preemptive goal programming (PGP) based multi-criteria decisionmaking methodology to consider both qualitative and quantitative factors in supplier selection. Wangphanich et al (2010) presented an analysis of the bullwhip effect in multi-product, multi-stage supply chain systems–a simulation approach. Wu (2002) presented a comparative study of using grey relational analysis in multiple attribute decision making problems
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