The optimization model of the vendor selection for the joint procurement from a total cost of ownership perspective
<p class="Abstract"><strong><em><span lang="EN-US">Purpose:</span></em></strong><span lang="EN-US"> This paper is an attempt to establish the mathematical programming model of the vendor selection for the joint procurement...
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| Format: | Article |
| Language: | English |
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OmniaScience
2015-09-01
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| Series: | Journal of Industrial Engineering and Management |
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| Online Access: | http://www.jiem.org/index.php/jiem/article/view/1551 |
| Summary: | <p class="Abstract"><strong><em><span lang="EN-US">Purpose:</span></em></strong><span lang="EN-US"> This paper is an attempt to establish the mathematical programming model of the vendor selection for the joint procurement from a total cost of ownership perspective. </span></p> <p class="Abstract"><strong><em><span lang="EN-US">Design/methodology/approach:</span></em></strong><span lang="EN-US"> Fuzzy genetic algorithm is employed to solve the model, and the data set of the ball bearings purchasing problem is illustrated as a numerical analysis.</span></p> <p class="Abstract"><strong><em><span lang="EN-US">Findings:</span></em></strong><span lang="EN-US"> According to the results, it can be seen that the performance of the optimization model is pretty good and can reduce the total costs of the procurement. </span></p> <p class="Abstract"><strong><em><span lang="EN-US">Originality/value:</span></em></strong><span lang="EN-US"> The contribution of this paper is threefold. First, a literature review and classification of the published vendor selection models is shown in this paper. Second, a mathematical programming model of the vendor selection for the joint procurement from a total cost of ownership perspective is established. Third, an empirical study is displayed to illustrate the application of the proposed model to evaluate and identify the best vendors for ball bearing procurement, and the results show that it could reduce the total costs as much as twenty percent after the optimization. </span></p> |
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| ISSN: | 2013-8423 2013-0953 |