Genetic Algorithm for Multi-Level Assembly Systems under Stochastic Lead Times

Abstract : The aim of this paper is to propose models to adapt and parameterize the Material Requirement Planning (MRP) approach under lead time uncertainty. Multi-level assembly systems with one type of finished products and several types of components aer studied. Each component has a fixed unit inventory cost and the finished product has a backlogging cost per unit of time. The lead times of components are discrete random variables, and the costumer’s demand of the finished product is known. A general mathematical model for supply planning of multi-level assembly systems is presented. A Genetic Algorithm (GA) method is proposed to minimize the sum of the average inventory holding cost for components and the average backlogging and inventory holding costs for the finished product.
Type de document :
Communication dans un congrès
19th IFAC World Congress, Aug 2014, Cape Town, South Africa. World Congress, Volume # 19 | Part# 1, p. 778-783, 2014, Proceedings of the 19th IFAC World Congress, 2014. 〈10.3182/20140824-6-ZA-1003.01522〉
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https://hal-emse.ccsd.cnrs.fr/emse-01083831
Contributeur : Florent Breuil <>
Soumis le : mardi 18 novembre 2014 - 10:23:37
Dernière modification le : jeudi 11 janvier 2018 - 06:16:31

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Oussama Ben Ammar, Alexandre Dolgui, Hélène Marian. Genetic Algorithm for Multi-Level Assembly Systems under Stochastic Lead Times. 19th IFAC World Congress, Aug 2014, Cape Town, South Africa. World Congress, Volume # 19 | Part# 1, p. 778-783, 2014, Proceedings of the 19th IFAC World Congress, 2014. 〈10.3182/20140824-6-ZA-1003.01522〉. 〈emse-01083831〉

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