A simulation-optimization approach for sales and operations planning in build-to-order industries with distant sourcing: Focus on the automotive industry

- We formulate a multi-objective optimization model for sales & operations planning.
- We present a simulation-optimization approach.
- The proposed solution is illustrated with the industrial case study of Renault.
- Several flexibility policies and optimization algorithms are compared.

Due to increasing globalization and distant sourcing, reconciling industrial constraints and sales requirements becomes very challenging for build-to-order industries facing an uncertain environment and demanding customers. 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 ε-constraints and is solved by a simulation-optimization approach. Two classes of policies 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, a French global automobile manufacturer. Several policies and optimization algorithms are compared in terms of system performance and computation time. Managerial insights are derived based on these results.