Are you interested in how mathematical optimization is driving better decision-making in today’s complex and data-rich environment? Join us on June 25 in Amsterdam for Gurobi Connect – Optimization in Practice, an afternoon event bringing together industry experts to explore how organizations are turning advanced analytics into real-world impact.

This session will highlight a range of applications—from energy systems and infrastructure planning to large-scale operational challenges—demonstrating how optimization delivers scalable, transparent, and high-value solutions across industries.

We will also explore how optimization fits within today’s AI landscape, working alongside machine learning and data-driven approaches to tackle complexity, improve efficiency, and support smarter decisions.

13:00: Welcome Remarks

13:15: Eneco Case Study

This session will be cover Heuristic portfolio optimization, ancillary and intraday market flex optimization and value of end to end VPP

14:00: Coffee Break

14:15: Lynx/Prorail Case Study

In order to fulfill the goals of the European Union to make international long-distance railway traffic more competitive to air traffic, it is necessary for all network and train operators to publish alternative timetables in case of maintenance much earlier in advance. The process of alternative timetabling is today largely done by manual planning, and now the RAAD optimizer will support the planners at ProRail to better handle the overwhelming workload.

15:00: CQM Case Study

In this session, we share how evolved customer expectations led us to apply Gurobi in large-scale transport planning challenges. After several years of successfully using a simulated annealing approach, evolving operational and customer requirements made more advanced optimization methods a significantly better fit. Together with a mobility service provider, we developed an optimization approach that improves vehicle occupancy, reduces empty kilometres and increases planning reliability for thousands of rides per day. We will present our journey including the practical challenges of balancing operational constraints, stakeholder interests and solution quality, and share lessons learned from applying mathematics in a real-world environment with social impact.

15:45: Prediction, Persuasion, and Proof 

Optimization has long offered a strong foundation for explainable decision-making. Its declarative models make assumptions, constraints, and trade-offs explicit, helping organizations understand not just what decision was made, but why. 

As machine learning and Generative AI become increasingly embedded in business processes, the question of trust has become even more important. How can we explain recommendations, validate outcomes, and ensure decisions remain aligned with business objectives? 

In this talk, we explore the evolution of explainability—from optimization models to modern AI systems—and discuss approaches such as counterfactual explanations. We show how machine learning, Generative AI, and optimization complement each other: AI can improve accessibility and generate insights, while optimization provides feasibility, transparency, and performance guarantees. Together, they help turn predictions into trustworthy decisions. 

16:30: Closing

16:45: Drinks & Networking

*Agenda is subject to slight changes without prior notice.

When?
Thursday, June 25

Where?

Venue Collective
Schoolstraat 2E, 1054 KD Amsterdam, Netherlands

• Please note that seats are limited, so restrictions may apply.

*Accommodation or airport transfers are not included.