TB1 - Exposé magistral 4 / Tutorial 4

Robust Optimization (RO) has emerged as a powerful mathematical framework for decision-making under uncertainty, providing tractable solutions that remain feasible under worst-case scenarios. This tutorial will provide an accessible yet comprehensive introduction to RO, drawing insights from key static and adjustable robust optimization methodologies. We will explore how these techniques can be applied across diverse domains, highlighting theoretical advancements and practical implementation challenges. Particular emphasis will be placed on logistics applications, demonstrating how RO methods enhance decision-making in humanitarian logistics, vehicle routing, and electromobility-based transportation systems. We will discuss applications in humanitarian relief distribution under uncertain travel conditions, reference work on robust needs assessment planning, and introduce recent research on electromobility-based vehicle routing that accounts for range anxiety and charging-station availability. Additionally, we will explore how adjustable robust optimization methods can improve decision-making in dynamic, uncertain environments, yielding more flexible and efficient outcomes. Through this tutorial, participants will gain a deeper understanding of RO techniques, learn best practices for defining uncertainty sets and implementing robust counterparts, and explore emerging opportunities in the intersection of robust optimization and sustainable logistics. The session will conclude with an interactive discussion on future research directions and real-world challenges in adopting robust optimization for large-scale and high-stakes decision-making.