A Simulation-Optimization approach for Managing the Sales and Operations Planning in the Automotive Industry
Résumé
The sales and operations planning (S&OP) is crucial for efficiently balancing production capacities with the volatile market demand. In this article, we propose an original S&OP model in order to improve the trade-off between the supply chain costs and the customer satisfaction. The problem is formulated as a multi-objective optimization model with $\epsilon$-constraints and is solved by a simulation-optimization approach. A static policy for managing the parts procurement and the flexibility offered to the sales function are presented. The model and the proposed solution are illustrated with the case study of Renault. Several optimization algorithms are compared in terms of system performance and computation time. Managerial insights are derived based on these results.