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Stochastic Models for Production/Inventory Planning: Application to Short Life-Cycle Products

Abstract : The phenomenon of uncertainty is encountered in many domains and should be faced. Even if the sources of this phenomenon are numerous, it is essentially due to our incapacity to predict precisely the future behaviour of a part or the whole of a given system. Many mathematical techniques have been emerged in the few last decades, which permit to master the uncertainty, and therefore to reduce our ignorance of how systems really behave.
In the Supply Chain Management domain, the main source of randomness is the future demand. This later is generally modelled using probability distribution functions, which are developed via different forecasting techniques. The influence of this demand variability on the performance of the Supply Chain is very important: for example, in 2007 the global inventory shortage rate in the retail industry were around 8.3%. On the other hand, in 2003 the global Unsaleable products cost around 1% in the grocery industry. These two types of costs, which are mainly caused by the uncertainty of the future demand, represent important lost for the whole Supply Chain actors.
This Ph.D. dissertation aims at developing mathematical production planning and inventory management models, which take into consideration the randomness of the future demand in order to reduce its economic negative impact, essentially for short life cycle products. We provide many planning models that consider the main issues of the planning problems, such as the production capacities, the information updating processes, the supply contracts and the advanced capacity reservation in a total costs minimization context. We consider in these models some aspects that are not considered in the literature, such as the “Payback” or the return options. We emphasize also on an important issue that characterize the globalization of the industry, which may be resumed in the difference between the procurement costs of the different suppliers. This issue is considered in the most chapters presenting models for short life cycle products and in the last chapter it is generalized to a long life cycle products setting. All the presented models are solved either analytically or numerically using the dynamic stochastic programming.
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Submitted on : Friday, April 25, 2008 - 2:28:03 PM
Last modification on : Wednesday, July 15, 2020 - 10:36:10 AM
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  • HAL Id : tel-00275821, version 1



Ali Cheaitou. Stochastic Models for Production/Inventory Planning: Application to Short Life-Cycle Products. Engineering Sciences [physics]. Ecole Centrale Paris, 2008. English. ⟨tel-00275821⟩



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