Come to Passau already on Tuesday (September 1) to take part in our Pre-Conference Program:
- Two workshops offered by our Gold Sponsors Guroby and Hexaly. These are open to all conference attendees.
- The PhD Program Dokt!OR aimed specifically at PhD students.
You can find more information about both programs below:
PhD Program Dokt!OR
Dokt!OR offers PhD students a unique opportunity to gain inspiration and practical insights to advance both their research and future careers in Operations Research. This year’s program brings together five sessions covering research and presentation skills, emerging connections between AI and OR, and diverse career paths within the OR community.
Join us on Tuesday, September 1, starting at 09:30 a.m. for an inspiring event.
Program
09:30-11:00 |  Workshop: Giving Better Presentations Christina Büsing The workshop Giving Better Presentations introduces key principles of effective scientific communication. Through an Euler presentation, participants first experience a deliberately poor presentation and then a well-designed version of the same content, highlighting common pitfalls and best practices. The workshop covers techniques for creating a strong opening, maintaining audience attention, using slides effectively, and improving delivery through body language, interaction, and clear structure. Practical exercises and discussions provide participants with concrete tools to enhance their own presentation skills and communicate their ideas more effectively. |
11:15-12:15 |  Workshop: Making an Impact Clemens Thielen This workshop will explore how Operations Research can create impact in practice. It will focus on how OR models, analytical methods, and decision-support approaches can inform and improve real-world decisions, tools, and processes. Based on examples and experiences from applied research projects, the workshop will address factors that can enable or hinder practical impact, such as problem selection, stakeholder involvement, model realism, usability, trust, and communication. It will also consider the relation between scientific depth and practical relevance, and why technically strong research does not automatically lead to practical adoption. Interactive elements will help participants reflect on the practical impact potential of their own research. |
Lunch Break |
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13:30-14:30 |  Tutorial: Automatic Heuristic Discovery: From DRL to LLMs Kevin Tierney In this tutorial, I will discuss the topic of automatic heuristic discovery, which is the task of creating custom heuristics to solve optimization problems. Starting from a deep reinforcement learning (DRL) perspective, I will cover the main mechanisms for directly predicting decisions of routing and scheduling problems. Following a look at DRL, I will turn to large language models (LLMs), which can also automatically design and code solution methods for optimization problems. The methods I will show match or beat state-of-the-art, human-designed heuristics on challenging routing and scheduling problems. The tutorial will end with ideas for integrating these methods into PhD student’s work. |
14:45-16:00 |  Master Class: Mixed Integer Optimization with Constraint Learning Dick den Hertog Many real-world optimization problems involve objectives and constraints that cannot be explicitly specified by mathematical formulas. For example, the effectiveness of a humanitarian intervention, the feasibility of a logistics plan, or the acceptability of a medical treatment may depend on complex relationships that are only partially understood but for which historical data are available. This raises a fundamental question: how can we optimize decisions when the optimization model itself must be learned from data? This master class introduces the emerging field of constraint learning, which combines machine learning and optimization to construct prescriptive models directly from data. We will discuss how predictive models, including linear models, decision trees, ensemble methods, and neural networks, can be embedded within mixed-integer optimization formulations, enabling the representation of complex objectives and constraints that are difficult or impossible to model analytically. A central challenge in this setting is reliability. Optimization algorithms tend to exploit imperfections in learned models, often leading to decisions in regions where little or no data are available. We will examine several approaches to addressing this issue, including trust-region methods that prevent harmful extrapolation and ensemble-based approaches that explicitly account for model uncertainty. The master class will present both the methodological foundations and practical applications of constraint learning, drawing on examples from humanitarian logistics and healthcare. Throughout the course, particular attention will be paid to the many open research questions that arise at the intersection of machine learning and optimization, making this a rich area for future PhD research. |
Coffee Break |
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16:30-18:00 | Panel Discussion: Careers in OR TBA Join us for an interactive session that is about your future! What pathways are there for a career in Operations Research, either in academia or in industry? Will we still need OR experts in the era of AI? Our panel of experts shed light on their individual experiences and take any questions you have.
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Sponsored Pre-Conference Workshops
„Smarter Modeling with Gurobipy“Speaker: TBATime and room: TBAAbstract: 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:
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„Modeling and Solving Routing Problems with Hexaly Studio“Speaker: Léa BlaiseTime and room: TBAAbstract: 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. |