Justine Broihan
Justine is a Senior Projects and Consulting Specialist at GAMS Software GmbH, where she bridges the gap between complex mathematics and practical software solutions. With a PhD in Operations Research and six years of experience in academic research and teaching, she now focuses on the end-to-end delivery of real-world optimization projects. For the past three years, Justine has been helping clients design, build, and deploy robust decision-making systems. She is passionate about showing developers how to move beyond basic heuristics and leverage true mathematical optimization to solve their most complex challenges.
Session
As Python developers, we frequently tackle complex decision-making problems by writing custom scripts and heuristic algorithms. While a standard greedy algorithm might provide a quick, intuitive fix, it rarely finds the best possible solution—often leaving significant efficiency, performance, and cost-savings on the table.
In this talk, we will explore the untapped power of mathematical optimization. We will start with a classic operations challenge. You will see firsthand how a standard rule-based Python heuristic compares to a mathematical optimization model, and how rigorously defining constraints and objectives can guarantee a globally optimal solution.
But optimization isn't just for traditional logistics! We will also bridge the gap to Machine Learning. We will demonstrate how optimization techniques can be utilized as a powerful verification step for ML models, such as calculating the minimum pixel changes required to trick a neural network into a misclassification.
While we can only scratch the surface of these vast topics, you will walk away with a fresh perspective on problem-solving. Whether you are automating business operations or building robust ML pipelines, you will learn when to graduate from basic heuristics and start leveraging the "art of the optimal".