Pre-Conference Workshop: „Smarter Modeling with Gurobipy“

Speaker: TBA

Time and room: TBA

Abstract: This hands-on workshop explores the powerful capabilities of gurobipy, Gurobi’s Python interface, with a focus on best practices and comparative analysis of different modeling paradigms. Participants will gain practical insights into different modeling flavors:

• Traditional Term-Based Modeling: The foundational approach using object-oriented constructs with variables, constraints, and expressions built iteratively.
• Matrix-Friendly API: Introduced in Gurobi 9.0 and enhanced through version 13.0, this paradigm leverages NumPy-style vectorization, broadcasting, and multi-dimensional operations.
• gurobipy-pandas: A convenience layer that allows mathematical model building directly out of DataFrames. The workshop is suitable for both optimization practitioners seeking to enhance their gurobipy skills and students who want to get started with modelling in gurobipy.

Prerequisites: Basic familiarity with Python and mathematical optimization concepts.

Pre-Conference Workshop: „Modeling and Solving Routing Problems with Hexaly Studio“

Speaker: Léa Blaise

Time and room: TBA

Abstract: Hexaly Optimizer is a global mathematical solver that integrates both exact and heuristic techniques to tackle complex optimization problems. At its core is an innovative modeling formalism based on nonlinear and set-oriented expressions, enabling users to write compact, expressive models for a wide variety of optimization problems. This formalism not only simplifies the modeling process but also provides the solver with higher-level structural information, allowing it to leverage advanced algorithmic techniques from the literature to obtain state-of-the-art performance on classic optimization domains such as routing, scheduling, and packing.

In this hands-on workshop, we will focus on the application of Hexaly to routing problems, showcasing how the solver’s set-based modeling capabilities naturally align with the structure of these problems. Participants will be guided through building and solving real-world routing problems using Hexaly Studio, a web-based integrated development environment designed specifically for optimization modeling. Hexaly Studio features intuitive dashboards, interactive widgets, and graphical solution visualizations, making it easy to both formulate models and interpret results. Through guided examples and interactive problem-solving, participants will gain hands-on experience with Hexaly and will be equipped to explore it further in their own research or applied projects.

Keynote: „Gurobi’s Primal-Dual Hybrid Gradient (PDHG) algorithm: practice and performance“

Speaker: Robert Luce

Time and room: TBA

Abstract: Gurobi’s Primal-Dual Hybrid Gradient (PDHG) algorithm has evolved rapidly since its introduction, with both the CPU and GPU backends having grown into production grade Gurobi features. In this session, we will share key insights from this exciting period of algorithmic innovation, including benchmarking results, customer success stories, and an overview of the technical capabilities of Gurobi’s PDHG implementation. We will also discuss where PDHG fits within the broader optimization landscape and the types of problems where it can deliver the greatest value.

Keynote: „Beyond MILP: Hexaly, a Hybrid Optimization Solver“

Speaker: Léa Blaise

Time and room: TBA

Abstract: Mixed Integer Linear Programming (MILP) has been the dominant optimization framework in Operations Research for several decades. While it has proven extremely powerful, it is also well known that MILP formulations can become unwieldy when confronted with large scale, highly combinatorial, non convex, or structurally rich problems, particularly in application domains such as routing, scheduling, and packing.

Hexaly is an industrial optimization solver built around a hybrid, post MILP approach. Rather than relying primarily on linearization techniques and classical branch and bound centered workflows, it combines heuristic and exact methods and draws inspiration from multiple paradigms, including Mixed Integer Programming, Constraint Programming, Nonlinear Programming, and Black Box Optimization. A central design objective is modeling expressiveness and openness: enabling users to formulate problems closer to their natural combinatorial structure, while allowing diverse algorithmic components to interact in a complementary manner.

In this talk, I will present the guiding principles behind this approach, with a particular focus on discrete optimization problems where Hexaly currently demonstrates its strongest performance, such as large scale routing, scheduling, and packing. I will discuss how hybridization manifests not only at the algorithmic level, but also within the modeling layer. Finally, I will provide a transparent overview of the solver’s current algorithmic status, supported by selected performance benchmarks.