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Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Session Overview
Location: Theresianum 0602

Date: Wednesday, 04/Sept/2024
11:00am - 12:00pm	WB 02: Learning for Optimization 1 Location: Theresianum 0602 Room Location at NavigaTUM Chair: Tobias Klein Learning to Filter State-Expanded Networks for Two-Stage Stochastic Programming Michael Römer Graph Convolutional Neural Network Assisted Monte Carlo Tree Search for the Capacitated Vehicle Routing Problem with Time Windows Jorin Dornemann, Tobias Klein, Kathrin Fischer, Anusch Taraz
1:00pm - 2:30pm	WC 02: Learning for Optimization 2 Location: Theresianum 0602 Room Location at NavigaTUM Chair: Maximiliane Rautenstrauß Learning the Follower's Objective Function in Sequential Bilevel Games Ioana Molan, Martin Schmidt, Johannes Thürauf Addressing Real-World Side Constraints in Combinatorial Optimization with Deep Reinforcement Learning Nayeli Gast Zepeda, Kevin Tierney, André Hottung Optimizing Ambulance Dispatching and Redeployment: A Structured Learning Approach Maximiliane Rautenstrauß, Maximilian Schiffer
3:00pm - 4:00pm	WD 02: Semiplenary Parmentier Location: Theresianum 0602 Room Location at NavigaTUM Chair: Maximilian Schiffer Recent Trends in Combinatorial Optimization Augmented Machine Learning Axel Parmentier
4:30pm - 6:00pm	WE 02: Metaparameter-Sensitivity, Heuristics and Data Integration in Machine Learning Location: Theresianum 0602 Room Location at NavigaTUM Chair: Sven F. Crone Beyond Instinct: Exploring Revenue Forecasting with Heuristics and Machine Learning Florian Artinger, Nikita Kozodoi, Julian Runge Integrating Large Citation Data Sets for Measuring Article’s Scientific Prestige Inci Yueksel-Erguen, Ida Litzel Sensitivity of Artificial Neural Networks for Metaparameters - an Empirical Evaluation on Sparse Data Sven F. Crone

Date: Thursday, 05/Sept/2024
8:30am - 10:00am	TA 02: Learning for Optimization 3 Location: Theresianum 0602 Room Location at NavigaTUM Chair: Heiko Hoppe Accelerating Constrained Shortest Path Subproblems in Column Generation Using Machine Learning Anne Schönhofen, Ulrich W. Thonemann On Graph Neural Networks for Column Generation with Multiple Pricing Problems Giacomo Dall'Olio, Yaoxin Wu, Rainer Kolisch Global Rewards in Multi-Agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems Heiko Hoppe, Tobias Enders, Quentin Cappart, Maximilian Schiffer
11:30am - 1:00pm	TC 02: Optimization for Learning Location: Theresianum 0602 Room Location at NavigaTUM Chair: John Alasdair Warwicker Towards Creating Robust Adversarial Examples for DNNs by MILPs Jörg Rambau, Ronan Richter Integrating Machine Learning with GAMSPy Hamdi Burak Usul A Mixed-Integer Linear Programming Framework for the Adversarial Training of Neural Networks John Alasdair Warwicker, Steffen Rebennack
2:00pm - 3:30pm	TD 02: Machine Learning for Supply Chain Optimization Location: Theresianum 0602 Room Location at NavigaTUM Chair: Bowei Gao Design End-to-End Supply Chain Optimization by Embedding Business Knowledge and Advanced Analytics Matej Lebl, Li Gan Towards a Sustainable Agri-Food Supply Chain by integrating Farm Management Decisions: Application of Hierarchical Reinforcement Learning Krunal Padwekar, Kanchan Awasthi, Subhas Chandra Misra Anomaly Detection and Operational Efficiency in Supply Chains Bowei Gao, Maximilian Moll, Stefan Pickl
4:00pm - 5:00pm	TE 02: Semiplenary Wallace Location: Theresianum 0602 Room Location at NavigaTUM Chair: Gudrun Kiesmüller Modeling with Stochastic Programming W. Wallace Stein

Date: Friday, 06/Sept/2024
8:30am - 9:30am	FA 02: Equilibrium Learning Location: Theresianum 0602 Room Location at NavigaTUM Chair: Kai Jungel Deep Reinforcement Learning for Equilibrium Computation in Multi-Stage Auctions and Contests Martin Bichler, Nils Kohring, Fabian Raoul Pieroth Fast and accurate approximations of traffic equilibria via structured learning pipelines Kai Jungel, Dario Paccagnan, Axel Parmentier, Maximilian Schiffer
9:45am - 10:45am	FB 02: Semiplenary Osorio Location: Theresianum 0602 Room Location at NavigaTUM Chair: Marie Schmidt Urban Transportation Simulation and Optimization: Large-Scale Network Modeling Meets Machine Learning Carolina Osorio
10:45am - 12:15pm	FC 02: Statistics and Machine Learning Location: Theresianum 0602 Room Location at NavigaTUM Chair: Thomas Setzer How to improve accessories sales forecasting of a medium-sized Swiss enterprise? A comparison between statistical methods and machine learning algorithms Agneta Ramosaj, Nicolas Ramosaj, Marino Widmer Ensembling Shrunk Weight Estimations in Forecast Combination Veronika Wachslander, Thomas Setzer Machine-Learning-based Determination of Steinian Shrinkage Targets and Levels in Forecast Combination Marco Fuchs, Thomas Setzer

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