Program for stream Data Science meets Optimization

MA-38: Automating the Design, Generation and Control of Optimization Algorithms 1
Stream: Data Science meets Optimization
Room: Michael Sadler LG19
Chair(s): Andrew J. Parkes, Ender Özcan

• Integrated optimization and machine learning: an application to predictive maintenance
  Marie Bouilloud, Michel Nakhla
• Data-Driven Constructive Metaheuristic for Combinatorial Problems
  Mariusz Kaleta, Tomasz Sliwinski
• Online Stochastic Generalized Assignment Problem with Delayed Demand Learning
  Hao Wang, Zihao Li, LIMENG LIU, Zhenzhen Yan
• Reinforcement learning-based iterated local search for the unrelated parallel machine scheduling problem
  Arthur Kramer, Ruan Myller Magalhães de Oliveira, Thiago Alves de Queiroz

MB-04: Interpretable Optimization Methods and Applications
Stream: Data Science meets Optimization
Room: Rupert Beckett LT
Chair(s): Patrick De Causmaecker, Sureyya Ozogur-Akyuz

• A SHAP-Driven Approach for Explainable Ensemble Pruning Using Semi-Infinite Programming
  Melisa Caliskan-Demir, Volkan Bakır, Sureyya Ozogur-Akyuz
• Game-theoretic Tree Regression for Surrogate-based Optimisation of Active Pharmaceutical Ingredient Manufacturing
  Artemis Tsochatzidi, Francesca Cenci, Magdalini Aroniada, Lazaros Papageorgiou
• Predictive performance and interpretability of machine learning algorithms compared to conventional mixed logit models in analyzing stated choice data
  Christoph Herrmann, Katharina Friederike Sträter
• Learn to Rank: Efficient Ranking and Visualisation of 4K Build Orientations for Surface Roughness Reduction in Additive Manufacturing
  Peizhi Shi, Yuchu Qin, Fanlin Meng, Ming Luo, Sajid Siraj

MB-38: Optimization in contexts with multi-media signals or data security
Stream: Data Science meets Optimization
Room: Michael Sadler LG19
Chair(s): Dimitri Papadimitriou, CHIEN CHU LU

• Forecast demand and scenarize energy production in district heating networks
  Slawomir Pietrasz, Marinette LOISY
• Integrating Machine-Learning in District Heating Networks
  Benjamin Dosse, Jérôme De Boeck, Bernard Fortz
• Using financial and network analytics to elucidate firm performance in the pharmaceutical industry
  Penina Orenstein, Rongrong Zhang
• Evaluating the optimal blockchain system of DRTS in eastern Taiwan
  CHIEN CHU LU, Cheng-Chieg (Frank) Chen

MC-04: Data science meets strongly NP-Hard CO
Stream: Data Science meets Optimization
Room: Rupert Beckett LT
Chair(s): Dimitri Papadimitriou, Woo Seok Goh

• Rethinking the Container Allocation Problem from a Machine Learning Perspective
  Kavitha Chetana Didugu
• Linear quasi-shrinkage estimator for high-dimensional optimization with linear constraints
  Naqi Huang, Nestor Parolya, Theresia van Essen
• Extremal graphs for star forests with bounded clique number
  Liying Kang
• Computational Analysis of DQN for the Binary Knapsack Problem
  Woo Seok Goh, Seyoung Oh, Kyungsik Lee

MC-38: Automating the Design, Generation and Control of Optimization Algorithms 2
Stream: Data Science meets Optimization
Room: Michael Sadler LG19
Chair(s): Ender Özcan, Andrew J. Parkes

• Genetic programming based algorithm for managing of rescue teams in crisis situations
  Adam Górski, Maciej Ogorzałek
• Designing branching strategies with genetic programming
  Simon Renard, Bernard Fortz, Quentin Louveaux
• Using Genetic Programming to generate Dispatching Rules for a Large-Scale Project Scheduling Problem
  Nuno Marques, Gonçalo Figueira, Luís Guardão, Luis Guimarães
• Online Resource Allocation Problem with Departures
  Yusuf Amidu

MD-38: (Deep) Reinforcement Learning for Combinatorial Optimization
Stream: Data Science meets Optimization
Room: Michael Sadler LG19
Chair(s): Yingqian Zhang, Kevin Tierney, Yaoxin Wu

• Direct action selection for solving the dynamic job shop scheduling problem with deep reinforcement learning
  Fynn Martin Gilbert, Kevin Tierney
• Static and Dynamic Policies for Multi-item Service Level Agreements with Finite Review Horizons and Penalty Costs
  Tarkan Temizoz, Christina Imdahl, Remco Dijkman, Douniel Lamghari-Idrissi, Willem van Jaarsveld
• Real-time capacity management in on-demand delivery platforms: A reinforcement-learning approach
  Gökhan Ceyhan, Pol Arias, Malte Winckler
• Beyond Optimality: Pragmatic AWS Instance Placement with Hexaly Solver
  Rubén Ruiz

TA-38: Forecasting, prediction and optimization 1
Stream: Data Science meets Optimization
Room: Michael Sadler LG19
Chair(s): Vittorio Maniezzo

• A Hierarchical Approach to Forecasting Censored Demand in Lost-Sales Systems
  Diego José Pedregal Tercero, Juan Ramon Trapero Arenas
• Estimating True Demand Under Stockouts and Interruptions: A Hybrid Tobit Kalman Filter and Conformal Prediction Approach
  Harsha Halgamuwe Hewage, Bahman Rostami-Tabar, Aris Syntetos
• Comparing traditional and machine learning methods on company cash flow forecasts in the logistics industry
  Alice Wolfe, Sarah Van der Auweraer, Kristof Coussement
• Enhancing Routine Immunisation Demand Forecasting: A Hybrid Probabilistic and Domain-Specific Approach
  Udeshi Salgado

TB-38: Forecasting, prediction and optimization 2
Stream: Data Science meets Optimization
Room: Michael Sadler LG19
Chair(s): Ahmed Kheiri, Sven Weinzierl

• Optimizing Forecasting Efforts: Focusing on What Really Pays Off
  Johann ROBETTE
• Integrated forecasting and optimization in multi-echelon logistics
  Vittorio Maniezzo, Livio Fenga
• Predictive and optimization-based package consolidation for efficient e-commerce fulfillment at Trendyol
  Mutlu Soruklu, Betül Ahat, MERT PARÇAOĞLU, Fikret Batu Sagay, Ahmet Çınar, Meltem Sanisoğlu
• A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis
  Sven Weinzierl, Sandra Zilker, Mathias Kraus, Patrick Zschech, Martin Matzner

TC-38: Forecasting, prediction and optimization 3
Stream: Data Science meets Optimization
Room: Michael Sadler LG19
Chair(s): Bahman Rostami-Tabar

• Good intentions, unintended consequences: Exploring forecasting harms
  Bahman Rostami-Tabar
• Optimizing Promotional Product Distribution in Retail with Machine Learning: A Decision Support Approach
  Eslem Guler Kose, Fatih Mehmet YILMAZ, Ebru Özcan, Ridvan Taylan
• A Predict-then-Optimize Framework for Traffic Allocation in Local Commerce Recommendation Systems
  Yani Ji, Yang Nan, Ran Ao, Yanting Jin, Ning Zhu, Zhu Meng, Jie Chen, YUN LONG
• A Quantum and Binary Incremental Learning Procedure for Categorical and Ordinal Classification
  Yueh LIN, Luis Perez, Stefano Nasini, Martine Labbé

TD-38: Foundation Models and Optimization
Stream: Data Science meets Optimization
Room: Michael Sadler LG19
Chair(s): Peer-Olaf Siebers, Yoon SUA

• Scenario Space Search for Two-Stage Stochastic Optimization Using Deep Generative Models
  Atefeh Hemmati Golsefidi, David Pisinger
• Improving Decommissioning of Offshore Platforms using Generative AI: An application of Large Language Models in the Oil and Gas industry
  Leonardo S. L. Bastos, Pedro Hamacher, Pedro Lobato, Gabriela Ribas Klein, Luidgi de Jesus da Silva Colimerio, Adriano Simões, ALEXANDER FERNANDES, Marcos Vinicius Marques da Silva, Vitor Sabbagh
• Generative AI Meets the Service Sector: A Study Using Topic Modeling
  Arkomita Mukherjee, M. P. Sebastian
• Contrastive Learning-based Semantic Embedding of Technology Groups
  Yoon SUA, Dohyun (Norman) Kim

WA-38: Industrial Optimization
Stream: Data Science meets Optimization
Room: Michael Sadler LG19
Chair(s): Grzegorz Pawlak

• SAT Information size and its implications for industrial optimization
  Maciej Drozdowski
• Multi-Objective Optimization Model for Strategic Acquisition of Additive Manufacturing Technologies
  Federica Tomelleri, Matteo Brunelli
• Financial Fraud Detection; Machine Learning; Data Balancing; Explainable AI; Transaction Networks
  Victor Chang
• AI-Driven Machine Learning Approach for Accurate Structural Modeling of Organic Light-Emitting Diodes
  InnJun Choi, Sung Woo Kang

WB-38: Optimization and Machine Learning: Methodological Advances
Stream: Data Science meets Optimization
Room: Michael Sadler LG19
Chair(s): Ender Özcan, Michael Römer

• Towards Convexity in Anomaly Detection: A New Formulation of SSLM with Unique Optimal Solutions
  Hao Wang
• Improved intuitionistic fuzzy least square twin support vector machine for class imbalance learning
  Yash Arora, S. K. Gupta
• Solving Polynomial Integer Programming with Hypergraph Neural Network
  Minshuo Li, Yaoxin Wu, Pavel Troubil, Yingqian Zhang, Wim Nuijten

WC-38: Optimization in Online Environments
Stream: Data Science meets Optimization
Room: Michael Sadler LG19
Chair(s): Grzegorz Pawlak

• Evaluating the Performance Impact of Data Sovereignty Features on Data Spaces
  Stanisław Galij, Grzegorz Pawlak, Slawomir Grzyb
• Optimal Grouping and Placement of Composite Parts in an Autoclave
  Tugce Yucel, Diclehan Tezcaner Öztürk, Murat Caner Testik
• Optimizing Transshipment Yard Operations in Railway Systems: A Hierarchical Approach to Enhancing Efficiency and Reducing Delays
  Grzegorz Pawlak, Jacek Blazewicz, Mateusz Cichenski, Erwin Pesch, Gaurav Singh

WD-38: Privacy-Aware and Optimization-Driven AI Systems
Stream: Data Science meets Optimization
Room: Michael Sadler LG19
Chair(s): Sureyya Ozogur-Akyuz, Polat Goktas

• Privacy-Preserving Robust Counterfactuals for Secure Model Interpretability
  Sureyya Ozogur-Akyuz, Volkan Bakır, Polat Goktas, Fatih Kahraman
• Analyzing Human Movement in Urban Spaces: The Influence of Cultural Venues, Green Infrastructure, and Fare Zones in London
  Jihye Hwang, Seongsoo Jang, Yuncheol Kang
• Optimizing pricing strategies through learning the market structure
  Khosroparviz Naderivarandi, Ezgi Karabulut, Burak Gokgur
• A Hybrid Matheuristic and Clustering Algorithm to Solve the Districting Problem in Public Bicycles Shared Systems
  Guillermo Cabrera-Guerrero, Pablo Andrés Maya Duque, Jalid Danoun, Carolina Lagos