At the meeting of the GOR working group "Analytics", Simon Mader presented recent research findings on the topic “A supervised machine learning framework to predict the request fit for dynamic dial-a-ride problems”. The presented work focuses on the intelligent selection of suitable passenger requests in rural on-demand bus systems. By combining machine learning and optimization techniques, the system becomes more efficient and enables more passengers to be transported overall, thereby improving mobility in rural areas.
The meeting was organized jointly by the Austrian Operations Research Society (ÖGOR) and the German Operations Research Society (GOR) in cooperation with the Austrian Federal Railways (ÖBB) in Vienna, Austria. With the topic “Transportation Analytics”, the program featured contributions in the areas of descriptive, predictive, and prescriptive analytics with applications in mobility and transport — ranging from the collection and analysis of mobility data to the planning and optimization of innovative transport solutions.