A Knowledge-based discrete event simulation approach for supplier selection with order allocation

Akram Zouggari 1 Lyès Benyoucef 1 Vipul Jain
1 COSTEAM - Optimal and secure management of manufacturing systems
Inria Nancy - Grand Est, UPVM - Université Paul Verlaine - Metz
Abstract : This paper presents a novel approach for automatic fuzzy based knowledge acquisition, which clubs supplier selection process with order allocation for dynamic supply chains to cope up with market variations. It imitates the knowledge acquisition and manipulation in a manner similar to that of decision makers who has gathered considerable knowledge and expertise in procurement domain. According to this concept, those decision criteria for supplier selection are considered first through four classes (CLASS I: Performance strategy, CLASS II: Quality of service, CLASS III: Innovation and CLASS IV: Risk), which are qualitatively meaningful. Thereafter, using fuzzy logic, the criteria application is quantitatively evaluated. As a result, the proposed approach generates knowledge for decision-making, and then, the developed combination of rules for supplier selection with order allocation can easily be interpreted, adopted and if necessary, modified by supply chain decision makers/practioners.
Type de document :
Communication dans un congrès
3rd IEEE International Conference on Industrial Engineering and Engineering Management - IEEM 2009, Dec 2009, Hong Kong, Hong Kong SAR China. IEEE, pp.1673 - 1678, 2009, 〈10.1109/IEEM.2009.5373133〉
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https://hal.inria.fr/inria-00599389
Contributeur : Ist Inria Nancy Grand Est <>
Soumis le : jeudi 9 juin 2011 - 16:13:35
Dernière modification le : mercredi 15 mars 2017 - 12:12:18

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Akram Zouggari, Lyès Benyoucef, Vipul Jain. A Knowledge-based discrete event simulation approach for supplier selection with order allocation. 3rd IEEE International Conference on Industrial Engineering and Engineering Management - IEEM 2009, Dec 2009, Hong Kong, Hong Kong SAR China. IEEE, pp.1673 - 1678, 2009, 〈10.1109/IEEM.2009.5373133〉. 〈inria-00599389〉

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