2026 ABRO Course on Advances in Operations Research
We are pleased to announce the 2026 ABRO Course on Advances in Operations Research, held this May at DIAG Sapienza in Rome. This year’s program features three specialized modules led by international experts, focusing on cooperative games, numerical optimization, and mixed-integer nonlinear programming.
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General Information
Dates: May 2026.
Location: Room B203 DIAG Sapienza, Via Ariosto 25, Rome.
Format: All lectures will be held in person.
Credits: Each module provides 3 ECTS (10 hours total per module).
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Module 1 | Cooperative Games: Basic Concepts and Case Studies
Instructor: Prof. Marcello Sanguineti (University of Genova).
Dates: May 4 – May 6, 2026.
Focus: An exploration of strategic interactions among agents. Topics include representation, stability, and fairness, with a specific look at the interplay between Machine Learning and Cooperative Games.
Applications: Case studies covering movement analysis, public transportation networks, and network congestion (Braess’ paradox).
| Session | Date | Time | Topic |
| Lecture 1 | 04/05/2026 | 14:00 - 17:00 |
A brief introduction to game theory. The role of cooperation. Representation of games.
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| Lecture 2 | 05/05/2026 | 11:00 - 13:00 |
Stability and fairness. Cooperative games on graphs. Network centrality.
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| Lecture 3 | 05/05/2026 | 14:00 - 16:00 |
Case studies: movement analysis, nonverbal communication, and public transportation networks.
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| Lecture 4 | 06/05/2026 | 10:00 - 13:00 |
Case studies: network congestion and Braess’ paradox.
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Module 2 | Proximal Methods in Numerical Optimization
Instructor: Dr. Alberto De Marchi (University of the Bundeswehr Munich).
Dates: May 4 – May 7, 2026.
Focus: An introduction to proximal methods, a family of algorithms essential for modern large-scale optimization. The course covers proximal-gradient methods and convergence analysis in nonconvex settings.
Applications: Challenges in data science, image processing, machine learning, and robotics.
| Session | Date | Time | Topic |
| Lecture 1 | 04/05/2026 | 11:00 - 13:00 |
Part I: Motivation and Background. Proximal operator and applications in data science, robotics, and finance.
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| Lecture 2 | 05/05/2026 | 09:00 - 11:00 |
Part II: Proximal Point Methods. Minimization problems involving prox-friendly terms.
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| Lecture 3 | 06/05/2026 | 14:00 - 16:00 |
Proximal Gradient Methods. Structured problems with differentiable and prox-friendly terms.
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| Lecture 4 | 07/05/2026 | 10:00 - 13:00 |
Nonsmooth Problems with Constraints. Penalty and barrier methods.
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Module 3 | Mixed Integer Non Linear Optimization: Methods and Applications
Instructor: Dr. Claudia D’Ambrosio (CNRS and École Polytechnique).
Dates: May 20 – May 22, 2026.
Focus: A deep dive into Mixed Integer Non Linear Optimization (MINLO), one of the most general classes of optimization problems. Lectures will cover fundamentals and methods for both convex and nonconvex MINLO.
Applications: Practical examples from energy systems, finance, and air traffic management.
| Session | Date | Time | Topic |
| Lecture 1 | 20/05/2026 | 14:00 - 17:00 |
Refresher on mathematical optimization, linear programming, and MILP; introduction to MINLO.
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| Lecture 2 | 21/05/2026* | 10:00 - 13:00 |
Convex MINLO and real-world applications.
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| Lecture 3 | 22/05/2026 | 09:30 - 13:30 |
Nonconvex MINLO: generic and tailored methods and real-world applications.
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[!NOTE] For more details or inquiries regarding specific modules, please contact the Veronica Piccialli Veronica.piccialli@uniroma1.it