Articles scientifiques

A Practical Implementation of Stochastic Programming: an Application to the Evaluation of Option Contracts in Supply Chains



mai 2004, vol. 40, n°5, pp.743-756

Départements : Informations Systems and Operations Management, GREGHEC (CNRS)

Stochastic programming is a powerful analytical method in order to solve sequential decision-making problems under uncertainty. We describe an approach to build such stochastic linear programming models. We show that algebraic modeling languages make it possible for non-specialist users to formulate complex problems and have solved them by powerful commercial solvers. We illustrate our point in the case of option contracts in supply chain management and propose a numerical analysis of performance. We propose easy-to-implement discretization procedures of the stochastic process in order to limit the size of the event tree in a multi-period environment.

Analyzing Variability in Continuous Processes

K. Rajaram, A. ROBOTIS

European Journal of Operational Research

juillet 2004, vol. 156, n°2, pp.312-325

Départements : Informations Systems and Operations Management

Author Keywords: continuous processes; production; variability; process design; operational improvement Abstract: We analyze the impact of variability on a continuous flow production process. To perform this analysis, we consider an n-stage, serial continuous process in which variability is introduced at each stage. We develop a continuous time model to capture the propagation of variability through the system and use this model to calculate the mean and the variance of the distribution of the output from this process. These results are then used to determine the optimal decisions for variability reduction when designing and operating these processes

Conception d'un projet de service dans une bureaucratie professionnelle : Le cas d'un projet immobilier et de soin


Sciences de Gestion

2004, n°45, pp.17-49

Départements : Informations Systems and Operations Management, GREGHEC (CNRS)

Efficient Scheduling RuleS in a Combined Make-to-Stock and Make-to-Order Manufacturing System

K. Youssef, C. VAN DELFT, Y. Dallery

Annals of Operations Reseach

février 2004, vol. 126, n°1-4, pp.103-134

Départements : Informations Systems and Operations Management, GREGHEC (CNRS)

In this paper, we consider a mixed MTS/MTO policy to manage a single manufacturing facility producing two classes of end-products. A few end-products have high volume demands, whereas a fairly large number of end-products have low volume demands. In this situation, it is appealing to try to produce the high volume products according to an MTS policy and the low volume products according to an MTO policy. The purpose of this paper is to analyze and compare the impact of the choice of the scheduling policy on the overall performance of the system. We consider two policies: the classical FIFO policy and a priority policy (PR). The PR policy gives priority to production orders corresponding to low volume products over production orders corresponding to high volume products. Under some simple stochastic modeling assumptions, we develop analytical/numerical solutions to optimise each system. We then provide insights regarding this issue with the help of numerical examples. It appears that for some range of parameters, the PR rule can outperform the FIFO rule in the sense that, to achieve the same service level constraint, the corresponding cost under the PR rule is much lower. This situation is encountered when the low volume products can be managed with an MTO policy under the PR scheduling rule, while they have to be managed according to an MTS policy under the FIFO scheduling rule. We also derive some theoretical properties that support our empirical findings.

Optimal server assignment for a multiple customer classes problem

J. Gonzalez, M. Norbis, L. KERBACHE

IMA Journal of Management Mathematics

juillet 2004, vol. 15, n°3, pp.195-210

Départements : Informations Systems and Operations Management, GREGHEC (CNRS)

The problem of assigning identical servers to different customer classes with the objectives of optimizing customer service and resource utilization is analysed. The problem that motivated this research is the assignment of batch jobs in a computer centre running the operating system MVS (Multiple Virtual Storage). A mathematical formulation of the problem is presented and its computational complexity discussed. A new schema for the definition of customer classes and a heuristic for the assignment of servers to classes are developed and applied to the problem. Numerical results show the efficiency of the procedure as compared with other previously utilized methods. The final part of the paper presents the conclusions and recommendations for further research


Informations Systems and Operations Management

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Woonam HWANG

Informations Systems and Operations Management

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