Conference Agenda

Realizing adaptive process chains - a practical example from the automotive sector

Elisabeth Jung, Michael Mayer, Magdalena Schober

Poverty analysis to identify household heterogeneity via deep clustering and Bayesian modeling of income and health expenditure using the GB2: blending machine learning analytics with uncertainty quantification techniques

Songul Cinaroglu, Sebastian Krumscheid

A Biobjective Perspective on Physics-informed Neural Networks

Lea Sophie Meissner

Non-Normal Distributions: A comparison of Reinforcement Learning Algorithms under various probability distributions

Maximilian Moll, Stefan Pickl

Optimizing Representativeness with a Novel Clustered Sampling Approach for Diverse Populations

Sohrab Mamdoohi

Collaborate for Good: Orchestrating Sustainability in Supply Chains

Tarkan Tan

Extended SPEC: Analysing Loss Functions for Forecasting Sparse Time Series

Joshua Arnold, Maximilian Moll, Stefan Pickl

Improving machine learning based time series forecasts: The relevance of short-run information for daily financial forecasts

Theo Berger

Multi-variate Density Estimation of Lead Time Demand

Robin Reiners, Florian Sachs, Ulrich Thonemann

Explainability and Interpretability in Mathematical Optimization

Michael Hartisch

Learning to solve combinatorial optimization problems with a decision tree

Kevin Tierney

Explainable Mathematical Optimization with Feature Selection

Kevin-Martin Aigner, Marc Goerigk, Michael Hartisch, Frauke Liers, Arthur Miehlich, Florian Rösel

Bridging the Gap: Explainable Optimization by Communicating Vessels

Miguel Krause, Sebastian Hien, Lena Klosik, Michael Kreimeier

Counterfactual Explanations for Optimization

Marc Goerigk, Jannis Kurtz, Sebastian Merten

OR for Everyone: Solving OR Problems as Non-Experts with Generative AI

Jörn Maurischat, Stephan Bogs, Grit Walther, Olaf Kirchhof

Operational Optimization of FttH Networks: A Data-Analytic Approach Using Clustering and Contract Theory

Mohamed Saâd EL HARRAB, Michel NAKHLA

CANCELLED: A top-weighted algorithm for comparing incomplete and non-conjoint rankings based on their correlation

Christoph Strauss, Lin Himmelmann, Daniel Politze, Remo Fankhauser, Andreas Ruckstuhl

Machine Learning Models to Optimize Energy Consumption of Electrical Locomotives

Fatih Kocatürk, Daniele Giannandrea, Gislind Stefan, Jan Fabian Ehmke

SDP-based Computational Strategies for Combinatorial Optimization

Angelika Wiegele

Co-Optimization of Energy and Reserves in European Energy Markets

Anthony Papavasiliou

A comparative analysis of Machine Learning Algorithms based on Meta-heuristic algorithms in Feature Selection for Imbalanced Datasets

Nimet Yapıcı Pehlivan, Özlem Akarçay Pervin, Muhammed Nurullah Kutlu, Halil Osman Erbek

Investigation of the impact of the time lag between training and test data sets on the accuracy of credit scoring models

Yanwen Dong, Noriki Ogura

Beyond the Crystal Ball: Unveiling the Power of Causal and Generative AI for Strategic Foresight

Elena Fitkov-Norris, Nataliya Kocheva