Based on an empirical study, this paper explicits the main features of the experience of supply chain management in France.

A fluid modeling approach is adopted in this paper to evaluate the performance indices such as the time to produce a given order (called the lead time) and the probability of meeting a customer order on time (called the fill rate) for a failure-prone production system. Lead time and fill rate estimations are very important in the context of Advanced Resources Planning approach, which is an ideal high-level tuning and planning tool to be used in various planning environments like MRP, ERP, JIT, Load-Oriented Planning, Theory of Constraints, POLCA systems, and Finite Scheduling. We derive closed forms expressions of the lead time and the fill rate for constant and variable demands. In the case of a constant demand, the derivation of the lead time average and variance uses a well known result on the first passage time of a Wiener process to a constant boundary, and the derivation of the fill rate is based upon Shuster’s derivation. In the case of a variable demand, the problem is solved by considering the first-passage time of Markov processes to moving boundaries as a first-exit time for a vector whose components include the process and the demand (i.e. the boundary). Thus when the demand is itself a solution of a differential equation, the theory of first-exit times for multidimensional processes is used to obtain differential equations for the moments and density of the first-passage time of the process to the boundary. Finally, we use a modified version of Park and Paranjape’s result and we investigate also the use of the theory of multidimensional diffusion processes to derive closed-forms expressions of the fill rate. An example of a cigarettes production line is used to illustrate the newly obtained analytical results.

Dans cette communication nous traitons de l’optimisation des décisions d’approvisionnement pour un détaillant d’un ensemble de produits saisonniers. La demande de ces produits est probabiliste et supposée indépendante. Les coûts de transport , de pénurie et de stockage de fin de saison son considérés. Le détaillant doit prendre ses décisions d’approvisionnement en tenant compte de contraintes budgétaires. Dans cette communication, nous présentons une revue de la littérature, ensuite nous introduisons une heuristique de résolution et finalement nous exposons les résultats numériques obtenus.

We introduce a heuristic which configures resources in a multi-stage business network offering personalized offers to consumers. The simulation-based heuristic seeks to minimize resource, inventory and service costs while respecting delivery delays, service levels, resource utilization and personalized offers. We applied the heuristic to a case in the personalized golf club industry.