Clustering and selecting suppliers based on simulated annealing algorithms |
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Authors: | ZH Che |
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Affiliation: | Department of Industrial Engineering & Management, National Taipei University of Technology, 1, Sec. 3, Chung-Hsiao E. Rd., Taipei 106, Taiwan, ROC |
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Abstract: | This study proposes two optimization mathematical models for the clustering and selection of suppliers. Model 1 performs an analysis of supplier clusters, according to customer demand attributes, including production cost, product quality and production time. Model 2 uses the supplier cluster obtained in Model 1 to determine the appropriate supplier combinations. The study additionally proposes a two-phase method to solve the two mathematical models. Phase 1 integrates k-means and a simulated annealing algorithm with the Taguchi method (TKSA) to solve for Model 1. Phase 2 uses an analytic hierarchy process (AHP) for Model 2 to weight every factor and then uses a simulated annealing algorithm with the Taguchi method (ATSA) to solve for Model 2. Finally, a case study is performed, using parts supplier segmentation and an evaluation process, which compares different heuristic methods. The results show that TKSA+ATSA provides a quality solution for this problem. |
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Keywords: | Supplier selection Supplier clustering _method=retrieve& _eid=1-s2 0-S0898122111009801& _mathId=si61 gif& _pii=S0898122111009801& _issn=08981221& _acct=C000069490& _version=1& _userid=6211566& md5=ef0755943dc0a67b6434f1ce9d2a91a5')" style="cursor:pointer K-means" target="_blank">" alt="Click to view the MathML source" title="Click to view the MathML source">K-means Simulated annealing Taguchi method Analytic hierarchy process |
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