Program

Welcome to the INFORMS TSL Workshop 2025.

We are delighted to present a rich lineup of plenary and keynote talks, alongside a variety of thematic sessions. Please stay tuned for detailed scheduling updates.

Timetable

	5/19 Mon		5/20 Tue		5/21 Wed
9:00-10:15	MA: Keynote		TA1: Logistics I	TA2: Learning III	WA1: Online Optimization	WA2: Mobility
10:15-10:30	Coffee Break		Coffee Break		Coffee Break
10:30-12:00	MB1: VRP I	MB2: Learning I	TB1: Logistics II	TB2: Learning IV	WB1: Data-Driven Optimization	WB2: Smart City
12:00-13:30	Lunch*		Lunch*		Lunch*
13:30-15:00	MC1: VRP II	MC2: Learning II	TC1: Delivery	TC2: Network Design
15:00-15:30	Coffee Break		Coffee Break
15:30-18:00	Palace Tour		National Assembly Tour
18:00-19:00			Conference Dinner

*(Lunch is on your own)

📌 Keynote Speech

Title: Intelligent Mobility with Physical AI

Abstract:
In this talk, Dr. Chang will share Kakao Mobility's strategy and vision for the Next Mobility (NEMO) program, which includes autonomous driving, robot delivery, and digital twin solutions. These innovations are expected to revolutionize the industrial ecosystem and impact daily life, emphasizing the role of Physical AI in transforming industries like autonomous driving and robotics.

Speaker: Dr. Christopher Chang

Affiliation: Kakao Mobility Corp. Senior Vice President, Next Mobility Labs Director

Biography:
Dr. Christopher Chang is Senior Vice President at Kakao Mobility Corp., overseeing strategy, R&D, and business development in areas such as autonomous systems, digital twins, and Urban Air Mobility (UAM). He has previously worked at Hyundai Motor, Samsung Electronics, Qualcomm, and NASA-JPL, and holds a Ph.D. in Electrical Engineering from Caltech.

🗓️ Program Schedule

Track	Presentation
MB1: VRP I	Advanced Neural Separation Algorithm for Capacity Inequalities Yoonju Sim, Hyeonah Kim, Changhyun Kwon
	Enabling Learning of Heterogeneity in Driver-Customer Interactions: Vehicle Routing with Driver-Dependent Service Times Christian Truden, Margaretha Gansterer, Dominic Loske
	Combining Column-Elimination with Column-Generation Andre Cire, Ricardo Fukasawa, Anthony Karahalios, Matheus Oliveira
MB2: Learning I	Enhancing Dynamic Pricing in Passenger Transportation Networks Using Offline Reinforcement Learning Claudius Steinhardt, Philipp Haubenblas, Dominik Erchhorn, Andreas Brieden
	A reinforcement learning approach for resource constrained project scheduling problem in field artillery operations Hyungjoo Cha, Jaewon Kim, Dongkyun Kim, Taesu Cheong
	Hierarchical Decomposition Framework for Steiner Tree Packing Problem Hanburn Ko, Minu Kim, Han-Seul Jeong, Sunghoon Hong
MC1: VRP II	A Reinforcement Learning Approach for the Dynamic Vehicle Routing and Scheduling Problem with Stochastic Requests and Time-dependent, Stochastic Travel Times Dawei Chen, Christina Imdahl, David Lai, Tom Van Woensel
	Robust Optimization Approach for Time Dependent Vehicle Routing Problem with Time Windows under Travel Time Uncertainty Dong Woon Jung, Byung Jun Ju, Byung Do Chung
	Solving the Min-Max Mixed-Shelves Picker Routing Problem with Hierarchical and Parallel Decoding Laurin Luttmann, Lin Xie
	The Iterative Chainlet Partitioning Algorithm for the Traveling Salesman Problem with Drone and Neural Acceleration Jae Hyeok Lee, Minjun Kim, Jinkyoo Park, Changhyun Kwon
MC2: Learning II	Preference learning for efficient bundle selection in horizontal transport collaborations Steffen Elting, Jan Fabian Ehmke, Margaretha Gansterer
	An ALNS Algorithm for the Capacitated Vehicle Routing Problem with a Zone Tariff Alexander Huebner, Niklas Turna, Manuel Ostermeier
	Hybrid Intelligent Transportation Systems with Reinforcement Learning for Fresh Produce Chirag Seth, Mehrdad Pirnia, James H. Bookbinder
	DIANA-Based Dynamic Sub-Zoning for Dynamic Multi-Compartment Vehicle Routing Problem in Reverse Logistics Golman Rahmanifar, Mostafa Mohammadi, Tom Van Woensel, Alireza Ashrafian
TA1: Logistics I	Stochastic Programming for Dynamic Temperature Control of Refrigerated Road Transport Francesco Giliberto, Rosario Paradiso, David Wozabal
	Real-Time Routing Cost Predictions for Time Slot Management Gustavo Hurovich, Lucas Veelenturf, Niels Agatz
	A Rank-Based Choice Approach for Capacity-Constrained Supply Chain Planning Jisoo Park, Walid Klibi, Benoit Montreuil
TA2: Learning III	Neural Genetic Operators for Combinatorial Optimization Hyeonah Kim, Sanghyeok Choi, Jiwoo Son, Jinkyoo Park
	A Deep Reinforcement Learning Framework for Truck Platoon Schedule Coordination Xinzhu Ren, Haoyu Mu, Xiaotong Sun
	Optimizing Real-Time Warehouse Order Picking with Deep Reinforcement Learning Sasan Mahmoudinazlou, Abhay Sobhanan, Hadi Charkhgard
TB1: Logistics II	Efficient Heuristics for Multi-Port-Multi-Deck Car Carrier Ship Loading Problem with Height Constraint Huijie Tang, Federico Berto, Chunbo Hua, Kyuree Ahn
	A Mixed Truck-and-Robot System with Parcel Return and Robot Reuse Tobias Huf, Manuel Ostermeier
	Smart Logistics: Multi-Attribute Bidding Optimization via Deep Reinforcement Learning Yuncheol Kang, Seokgi Lee, Daiki Min
TB2: Learning IV	Fast Shapley value approximation through machine learning with application in routing problems Johannes Gückel, Pirmin Fontaine
	Dynamic Time Slot Management and Vehicle Dispatching Problem with Machine Learning Sifa Çelik, Albert Schrotenboer, Layla Martin, Tom Van Woensel
	Hypernetwork-Based Concurrent Learning of Optimal Composition Design for Partially Controlled Multi-Agent Systems Kyeonghyeon Park, David Molina Concha, Hyun-Rok Lee
	Urban Region Embedding via Mobility Time Series Contrastive Learning Namwoo Kim, Takahiro Yabe, Chanyoung Park
TC1: Delivery	Neural-Network Aided Optimization for On-Demand Food-Delivery Services with a Mixed Fleet of Drones and Human Yang Liu, Sen Li
	The Pickup and Delivery Problem with Configurations Casper Bazelmans, Albert Schrotenboer, Gilbert Laporte, Tom Van Woensel
	Feasibility Assessment in Attended Home Delivery with Basket Uncertainty Remy Spliet, Liana van der Hagen, Niels Agatz
TC2: Network Design	Learning-based simulation-optimization for service network design under uncertainty Javier Durán-Micco, Bilge Atasoy
	Combined Natural Gas and Hydrogen Pipeline Network Design Gerben Ouwersloot, Albert Schrotenboer, Zümbül Atan
	Traffic Network Layout Optimization with Diffusion Models Taeyoung Yun, Yujin Shin, Inhyok Song
WA1: Online Optimization	Classification-based Learning for the Online On-demand Warehousing Problem Margaretha Gansterer, Alessio Sclafani, Simona Mancini, Sara Ceschia, Antonella Meneghetti
	Multi-Camera Predictive Traffic Sensing via Transformer-Enabled Constrained Correlated Online Learning Tao Li, Quanyan Zhu
	Online Container Allocation and Dynamic Rebalancing with Deep Reinforcement Learning Emre Kara, Layla Martin, Mehrdad Mohammadi, Willem van Jaarsveld
WA2: Mobility	Fair Fares for Vehicle Sharing Systems Adam Elmachtoub, Hyemi Kim
	A predict-then-optimize approach for solving a first-and-last-mile ridesharing problem Bo Sun, Si Zhang, Qiang Meng
	Integrating Latent Urban Factors in Vertiport Site Selection: A Comprehensive Framework and Seoul Case Study Sungmin Sohn, Namwoo Kim, Mark Hansen, Yoonjin Yoon
WB1: Data-Driven Optimization	Data-Driven Bunker Refueling Under Price Uncertainty Qinghe Sun, Mabel Chou
	Optimal Planning for Electric Vehicle Public Charging Infrastructure: A Case Study in New York City Yichan An, Joseph Chow, Soomin Woo, Jinwoo Lee
	Data-driven optimization for wildfire suppression resource deployment: A case study of Alberta Wildfire Yasser Zeinali, Ilbin Lee, Mostafa Rezaei, Armann Ingolfsson
WB2: Smart City	Dynamic Berth Allocation Policies in the Deep-Sea Terminals Behman Orkun Tunay, Pieter van den Berg, Rob Zuidwijk
	Single-Vehicle Residential Waste Collection Problem with Turn Penalty, Visual Attractiveness Seungyeop Lee, Sangil Han, Byung-In Kim
	Integrating Urban Air Mobility with Highway Infrastructure: A Strategic Approach for Vertiport Location Selection in the Seoul Metropolitan Area Donghyun Yoon, Minwoo Jeong, Jinyong Lee, Seyun Kim, Yoonjin Yoon