Summer School 2026 – Artificial Intelligence and Optimization: From Mathematical Modelling to Hybrid and Learning-Based Approaches
Dear colleague,
We are pleased to announce the 2026 Summer School on Hybrid Metaheuristics with Learning Approaches, taking place June 29 – July 2, 2026 at the Université de Haute-Alsace (France).
This 4-day intensive program will explore modern optimization methods at the intersection of Artificial Intelligence, Operations Research, and Data Science.
Many real-world optimization problems—arising in logistics, energy systems, transportation, and healthcare—are large-scale, nonlinear, and highly constrained. To address these challenges, researchers increasingly rely on hybrid approaches combining mathematical optimization, metaheuristics, and machine learning.
What participants will learn:
- Mathematical modeling and exact optimization methods (MILP, Gurobi)
- Metaheuristics and approximate algorithms
- Machine learning for data-driven optimization
- Surrogate models for computationally expensive problems
- Hyper-heuristics for algorithm selection and generation
Participants will work on a practical case study on Electric Vehicle Charging Scheduling (EVCS), illustrating how hybrid AI approaches can address emerging challenges in sustainable mobility and enregy systems.
Final Challenge:
On the last day, participants will take part in a hands-on optimization challenge based on the EVCS problem.
Three prizes will be awarded to the best performing solutions.
Target audience:
PhD students, early-career researchers, R&D engineers, and faculty members working in AI, Optimization, Operations Research, and Data Science.
More information and registration: https://omega-irimas.github.io/summer-school-2026/
Participation is limited to 30 participants to ensure an interactive learning experience.
Application deadline: May 15, 2026.
Scientific Committee:
Ammar Oulamara – University of Lorraine
Diego Oliva – University of Guadalajara
Ed Keedwell – University of Exeter
Abdennour AZERINE – Université de Haute-Alsace
Mahmoud Golabi (HDR, Ph.D.) Golabi – Université de Haute-Alsace
Lhassane Idoumghar – Université de Haute-Alsace
Pierrick Legrand – University of Bordeaux
Evelyne Lutton – INRAE
Nicolas Monmarché – University François Rabelais of Tours
Denis Pallez – Université Côte d’Azur
Please feel free to share with colleagues and students interested in advanced optimization and hybrid AI methods.
Lhassane IDOUMGHAR, Pr. HDR. PhD.