Abstract

This thesis examines how robust optimization can address the operational uncertainties faced by APIA, a major Moroccan olive oil producer. In an industry marked by fluctuating yields, shifting costs, and unpredictable market demand, robust optimization provides a practical approach to making decisions that remain reliable and nearly optimal, even when conditions change. The model developed in this research incorporates robust optimization techniques into APIA’s operations, balancing strategic long-term planning with the need for real-time adaptability. By allowing for scenario-based flexibility, the model tailors the level of conservatism to reflect specific uncertainties, ensuring solutions are both practical and resilient, even under worst-case scenarios. Scalable and computationally efficient, the model developed is designed to support key operational decisions in procurement, production, transportation and storage. Through numerical experiments, this thesis demonstrates how the model helps optimize APIA’s operations, reducing costs while maintaining operational stability. By managing variability effectively, this research offers APIA a strategic tool to navigate the complexities of the agro-industrial sector, improve profitability, and achieve sustainable growth.
Keywords: robust optimization, operational parameter uncertainty, olive oil supply chain.