Mixed Integer Programming (MIP) Workshop 2026 Stamford, USA

Events

Marion Technical Writer April 24, 2026

Hexaly is delighted to be the Platinum Sponsor of Mixed Integer Programming (MIP) Workshop 2026 . The MIP Workshop is a single-track workshop highlighting the latest trends in integer programming and discrete optimization, with speakers chosen by invitation. The event will take place from May 18 to 21, 2026, at University of Connecticut – Stamford Campus, USA. You can access the conference program here.

Come visit the Hexaly booth and meet Fred Gardi, Founder & CEO of Hexaly, who will be on-site throughout the day. He will be happy to connect if you have questions, want to learn more about our technology, or are curious about the latest features of Hexaly 14.5. This new version 14.5 brings major performance improvements in routing, scheduling, and packing, along with a significant boost in nonlinear optimization capabilities. It is also a great opportunity to discuss career opportunities at Hexaly in an informal setting. Below are the abstracts of Fred’s talks at the 2026 Mixed Integer Programming (MIP) Workshop:

Beyond MILP: Hexaly, a Hybrid Optimization Solver
Fred Gardi, Founder & CEO, Hexaly – Wednesday, May 20, 2026, 3:40-4:15 p.m

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—crucially—within the modeling layer. Finally, I will provide a transparent overview of the solver’s current algorithmic status, supported by selected performance benchmarks.

We look forward to connecting with the Operations Research community at the 2026 MIP Workshop in Stamford, USA.

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