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Program for stream Data Science Meets Optimization
Sunday
Monday
Monday, 8:30-10:00
MA-03: Industrial Optimization
Stream: Data Science Meets Optimization
Room: 1005 (building: 202)
Chair(s):
Grzegorz Pawlak
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Research on Optimization of Air Material Joint Allocation under Multi-level Inventory Model
CHENYANG WANG, Jianwu Xue, Jiawei Tuo -
Classifying import containers based on cargo contents: an unsupervised text classification
Ying Xie, Dongping Song -
Long-term maintenance optimization for integrated mining operations
Yingying Yang -
Approximate dynamic programming for inland empty container inventory management
Sangmin Lee, Trine Krogh Boomsma
Monday, 10:30-12:00
MB-03: Optimization in Online Environments
Stream: Data Science Meets Optimization
Room: 1005 (building: 202)
Chair(s):
Grzegorz Pawlak
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Multi-objective optimal recommender systems
Elaheh Lotfian, Alireza Kabgani -
Bidding in Online Display Advertising: A Deep Reinforcement Learning Model for Mobile Gaming Market
Qirui YANG, Frank Chen, Mengzhuo GUO, Houmin Yan, Qingpeng ZHANG -
An Algorithmic Approach to Managing Supply Chain Data Security: The Differentially Private Newsvendor
Du Chen, Geoffrey A. Chua -
Applying Mathematical Programming to Visualize Text Summarization from Multiple Perspectives
Li-Ching Ma
Monday, 12:30-14:00
MC-03: (Deep) Reinforcement Learning for Combinatorial Optimization 1
Stream: Data Science Meets Optimization
Room: 1005 (building: 202)
Chair(s):
Yingqian Zhang, Kevin Tierney
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PPSTOW: An End-to-End Deep Reinforcement Learning Model for Master Stowage Planning on Container Vessels
Jaike van Twiller, Djordje Grbic, Rune Jensen -
A Tale of Middle-Mile Logistics, Graph Neural Networks, and Reinforcement Learning
Thibaut Cuvelier, Onno Eberhard, Bruno De Backer -
Addressing Real-World Side Constraints in Combinatorial Optimization with Deep Reinforcement Learning
Nayeli Gast Zepeda, Kevin Tierney, André Hottung -
Learning Efficient and Fair Policies for Collaborative Human-Robot Order Picking
Igor Smit, Zaharah Bukhsh, Yingqian Zhang
Monday, 14:30-16:00
MD-03: (Deep) Reinforcement Learning for Combinatorial Optimization 2
Stream: Data Science Meets Optimization
Room: 1005 (building: 202)
Chair(s):
Kevin Tierney, Yingqian Zhang
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PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization
André Hottung, Kevin Tierney -
A regression model for selecting effective cuts in a Branch-and-Cut algorithm
Marcello Sammarra, Giovanni Giallombardo, Giovanna Miglionico -
Learning to Branch in Combinatorial Optimization with Graph Pointer Networks
Bo Jiang, Rui Wang, Gang Zhou -
Learning to solve combinatorial optimization problems with a decision tree
Kevin Tierney
Tuesday
Tuesday, 8:30-10:00
TA-03: (Deep) Reinforcement Learning for Combinatorial Optimization 3
Stream: Data Science Meets Optimization
Room: 1005 (building: 202)
Chair(s):
Yingqian Zhang, Kevin Tierney
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Optimizing a Multi-echelon, Multi-Product, Lost-Sales Inventory Management System through Deep Reinforcement Learning
Fatemeh Fakhredin, Joern Meissner -
Learning to Generate Hard Instances: Towards Robust Solutions for Vehicle Routing Problems
Xia Jiang, Yaoxin Wu, Yingqian Zhang -
AM4FJSSP: An Attention Model formulation for the Flexible Job Shop Scheduling Problem
Lin Xie -
Job Shop Scheduling Benchmark: Environments and Instances for Learning and Non-learning Methods
Yingqian Zhang, Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh
Tuesday, 10:30-12:00
TB-03: Machine Learning in Applied Optimization
Stream: Data Science Meets Optimization
Room: 1005 (building: 202)
Chair(s):
Michael Römer
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Learning optimal courier assignments in on-demand delivery platforms
Gökhan Ceyhan, Pol Arias -
A DECISION SUPPORT FRAMEWORK FOR AUTOMATED REVIEWER ASSIGNMENT USING NLP AND OPTIMIZATION
Meltem Aksoy, Seda Yanık, Mehmet Fatih Amasyali -
Harnessing the Power Trained Reinforcement Learning Agents in Job Shop Scheduling Problems
Constantin Waubert de Puiseau, Hasan Tercan, Tobias Meisen -
Decision-focused learning with machine learning proxies for energy storage system optimization in energy markets
Ruben Smets, Mathieu Tanneau, Jean-François Toubeau, Kenneth Bruninx, Pascal Van Hentenryck, Erik Delarue
Tuesday, 12:30-14:00
TC-03: Optimization and Machine Learning: Methodological Advances
Stream: Data Science Meets Optimization
Room: 1005 (building: 202)
Chair(s):
Michael Römer
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Mixed Integer Programming and Heuristics Approaches for Clustering with Local Feature Selection
Cem Iyigün -
Anytime algorithm configuration
Elias Schede, Kevin Tierney -
Using Clustering to Strengthen Decision Diagram Bounds for Discrete Optimization
Michael Römer, Mohsen Nafar
Tuesday, 14:30-16:00
TD-03: Data science meets strongly NP-Hard CO
Stream: Data Science Meets Optimization
Room: 1005 (building: 202)
Chair(s):
Dimitri Papadimitriou
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Provably convergent algorithm for free-support Wasserstein barycenter of continuous non-parametric measures
Qikun Xiang, Zeyi Chen, Ariel Neufeld -
A Novel Criterion for Batch Size Adaptation in Stochastic Gradient Methods
Marco Boresta, Alberto De Santis, Stefano Lucidi -
Data-Driven Submodular Set-function Optimization: Theory and Applications in Assortment Planning and Recommender Systems
Jigar Patel
Wednesday
Wednesday, 8:30-10:00
WA-03: Data Science and Optimization
Stream: Data Science Meets Optimization
Room: 1005 (building: 202)
Chair(s):
Ender Özcan, Andrew J. Parkes, Chang Liu
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Integration of Operations Research (OR) and Machine Learning (ML) – A Literature Review
Francis Miranda -
Optimizing Post-Disaster Recovery Strategies in Telecommunication Network Infrastructure
Mohamed Saâd El Harrab, Michel Nakhla -
Unit Commitment Predictor
Farzaneh Pourahmadi -
Rise of Conscious Consumers: Impacts of Corporate Workplace Equality on Household Spending
Chang Liu
Wednesday, 10:30-12:00
WB-03: Interpretable Optimization Methods and Applications
Stream: Data Science Meets Optimization
Room: 1005 (building: 202)
Chair(s):
Patrick De Causmaecker
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Feature-Based Interpretable Optimization
Sebastian Merten, Marc Goerigk, Michael Hartisch, Kartikey Sharma -
Explainability and Interpretability in Mathematical Optimization
Michael Hartisch -
Leveraging Contextual Information for Robustness in Vehicle Routing Problems
Irfan Mahmutogullari, Tias Guns