A simulation optimization methodology for supplier selection problem
Identifieur interne : 000965 ( Hal/Corpus ); précédent : 000964; suivant : 000966A simulation optimization methodology for supplier selection problem
Auteurs : Hongwei Ding ; Lyès Benyoucef ; Xiaolan XieSource :
- International Journal of Computer Integrated Manufacturing [ 0951-192X ] ; 2005.
English descriptors
- mix :
Abstract
Strategic sourcing plays a critical role in supply chain planning. Supplier selection is one of the decisions that determine the long-term viability of a company. In this paper, a new simulation optimization methodology is presented to make decisions on supplier selection. The methodology is composed of three basic modules: a genetic algorithm (GA) optimizer, a discrete-event simulator and a supply chain modelling framework. The GA optimizer continuously search different supplier portfolio and related operation parameters. Corresponding simulation models are automatically created through an object-oriented process. After simulation runs, the fitness value of candidate supplier portfolio is derived from the estimations of key performance indicators (KPI). The fitness is returned to the GA to be utilized in searching the next prominent direction. By using the proposed methodology, the supply chain planner is able to optimize the supplier portfolio with taking uncertainties into consideration. Finally, a real-life case study is presented to illustrate the applicability of the proposed methodology. Experimental results are presented and analysed.
Url:
DOI: 10.1080/0951192052000288161
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Hal:emse-00449389Le document en format XML
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<front><div type="abstract" xml:lang="en">Strategic sourcing plays a critical role in supply chain planning. Supplier selection is one of the decisions that determine the long-term viability of a company. In this paper, a new simulation optimization methodology is presented to make decisions on supplier selection. The methodology is composed of three basic modules: a genetic algorithm (GA) optimizer, a discrete-event simulator and a supply chain modelling framework. The GA optimizer continuously search different supplier portfolio and related operation parameters. Corresponding simulation models are automatically created through an object-oriented process. After simulation runs, the fitness value of candidate supplier portfolio is derived from the estimations of key performance indicators (KPI). The fitness is returned to the GA to be utilized in searching the next prominent direction. By using the proposed methodology, the supply chain planner is able to optimize the supplier portfolio with taking uncertainties into consideration. Finally, a real-life case study is presented to illustrate the applicability of the proposed methodology. Experimental results are presented and analysed.</div>
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<hal api="V3"><titleStmt><title xml:lang="en">A simulation optimization methodology for supplier selection problem</title>
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<surname>Ding</surname>
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<author role="aut"><persName><forename type="first">Lyès</forename>
<surname>Benyoucef</surname>
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<author role="aut"><persName><forename type="first">Xiaolan</forename>
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<email>xie@emse.fr</email>
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<editor role="depositor"><persName><forename>Andrée-Aimée</forename>
<surname>Toucas</surname>
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<idno type="halRefHtml">International Journal of Computer Integrated Manufacturing, Taylor & Francis, 2005, 18 (2-3), pp.210-224. <10.1080/0951192052000288161></idno>
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<idno type="stamp" n="INPL">Institut National Polytechnique de Lorraine</idno>
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<sourceDesc><biblStruct><analytic><title xml:lang="en">A simulation optimization methodology for supplier selection problem</title>
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<title level="j">International Journal of Computer Integrated Manufacturing</title>
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<term xml:lang="en">analytic hierarchy process</term>
<term xml:lang="en">multiobjective approach</term>
<term xml:lang="en">choice strategies</term>
<term xml:lang="en">decision-support</term>
<term xml:lang="en">vendor selection</term>
<term xml:lang="en">management</term>
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<abstract xml:lang="en">Strategic sourcing plays a critical role in supply chain planning. Supplier selection is one of the decisions that determine the long-term viability of a company. In this paper, a new simulation optimization methodology is presented to make decisions on supplier selection. The methodology is composed of three basic modules: a genetic algorithm (GA) optimizer, a discrete-event simulator and a supply chain modelling framework. The GA optimizer continuously search different supplier portfolio and related operation parameters. Corresponding simulation models are automatically created through an object-oriented process. After simulation runs, the fitness value of candidate supplier portfolio is derived from the estimations of key performance indicators (KPI). The fitness is returned to the GA to be utilized in searching the next prominent direction. By using the proposed methodology, the supply chain planner is able to optimize the supplier portfolio with taking uncertainties into consideration. Finally, a real-life case study is presented to illustrate the applicability of the proposed methodology. Experimental results are presented and analysed.</abstract>
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