Optimisation for the Masses: No-Code, No-Math Modelling of Decision Problems

The Distinguished Lecture Series in Business Analytics & Data Science at Kühne Logistics University (KLU) presents public lectures on selected topics in analytics, data science, and their applications across various industries, including logistics and supply chain management. Targeted at students, alumni, industry professionals, and other interested individuals, the series offers insights into the latest advancements, trends, and challenges in these fields. Attendees gain valuable knowledge on how data-driven decision-making can transform business operations and enhance efficiency in today's digital economy.

Optimisation for the Masses: No-Code, No-Math Modelling of Decision Problems

Despite significant advancements in optimisation algorithms, their application remains limited to a narrow range of decision problems within businesses and organisations. Contributing to this gap between algorithmic innovation and practical usage is the complexity of translating real-world constraints into mathematical models required in order to be able to apply off-the-shelf optimisation solvers. Developing custom-made optimisation algorithms, as an alternative, demands substantial upfront investment and ongoing maintenance to ensure compatibility with evolving business needs. If such maintenance and adjustments are not done continuously, a significant technical debt can accumulate weakening overall competitiveness. This presentation shows how domain experts without expertise in mathematical modelling or programming can formulate and maintain decision problems graphically, providing all the information that is needed to apply algorithms for solving respective optimisation problems.

Event free of charge

Register now!

You may watch the series online via Zoom if you are not in Hamburg, Germany:

Join Zoom Meeting: https://the-klu-org.zoom.us/j/94860863146

Meeting ID: 948 6086 3146

If dialing in via telephone: find your local number HERE.

Learning to Optimize: How machine learning drives decision at companies like Uber

April 2nd, 2025 at 6 p.m. with Arne Heinold, Assistant Professor for Transportation