Genetic algorithm for multi-level assembly systems under stochastic lead times

Abstract : The aim of this paper is to propose tools to adapt and parameterize the Material Requirement Planning (MRP) method under lead time uncertainty. We study multi - level assembly systems with one type of finished products and severa l types of components. We consider that 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 p roduct 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
The 19th World Congress of The International Federation of Automatic Control, Aug 2014, Cape Town, South Africa. 6p, 2014
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https://hal-emse.ccsd.cnrs.fr/emse-01063244
Contributeur : Florent Breuil <>
Soumis le : jeudi 11 septembre 2014 - 16:31:17
Dernière modification le : dimanche 28 janvier 2018 - 15:22:05

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  • HAL Id : emse-01063244, version 1

Citation

Oussama Ben Ammar, Alexandre Dolgui, Hélène Marian. Genetic algorithm for multi-level assembly systems under stochastic lead times. The 19th World Congress of The International Federation of Automatic Control, Aug 2014, Cape Town, South Africa. 6p, 2014. 〈emse-01063244〉

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