Despite significant advancements in optimization 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 optimization solvers. Developing custom-made optimization 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 optimization problems.

Have you ever wondered why and where taxi cars wait, or how smart Uber drivers make their decisions? This talk will delve into these intriguing questions. We will explore the concept of sequential decision-making and policy classes through a hands-on approach. Using taxi services as an example, we learn how service providers can optimize their decision-making. And guess what? There´s not as much magic behind it as you might think...so prepare to be surprised!