Call for Abstracts

We invite submissions for our upcoming workshop, focused on advancing the integration of machine learning (ML) and operations research (OR) to tackle complex challenges in transportation and logistics. With the growing need for intelligent, data-driven solutions, this workshop aims to bring together researchers and practitioners from both ML and OR communities to explore collaborative approaches and methods that leverage the strengths of each field.

• Main Theme: The interplay of machine learning and operations research for transportation and logistics challenges.

This workshop seeks to highlight innovative research that demonstrates how ML and OR can complement and enhance one another for tackling modern transportation and logistics challenges, with examples including but not limited to:

• Integration of ML-based data analysis with OR modeling to improve prediction, optimization, and decision-making in transportation.
• Development of end-to-end ML approaches to solve traditionally OR-based problems, offering new efficiencies and perspectives.
• Hybrid models that intertwine ML and OR methods for complex problem-solving, addressing areas where conventional OR or ML alone may fall short.
• Decision-focused learning frameworks that emphasize optimization-driven learning objectives tailored to real-world logistical applications.
• Exact or heuristic optimization algorithms enhanced by ML methods
• Innovative applications of large language models (LLMs) to transportation and logistics challenges.

We welcome any applications in the field of transportation science and logistics. Additionally, submissions of other methods and applications that are of traditional interest to INFORMS TSL Society members are encouraged, though priority will be given to abstracts that align better with the main theme of the workshop.

Submission Details

Please submit a 2–4 page extended abstract that provides a detailed summary of the research problem, methodology, and key findings or expected contributions. Submissions will be reviewed by a committee of experts, and selections will be based on relevance to the workshop theme, novelty, and potential impact.

Please refer to the workshop website for the submission abstract template.