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Machine Learning for Evolutionary Computation - Solving the Vehicle Routing Problems (ML4VRP)

Deadline: 2026-06-13
Webpage: https://sites.google.com/view/ml4vrp

Description

This competition aims to bring together the latest advances of machine learning-assisted evolutionary algorithms for solving vehicle routing problems (VRP). Current relevant research has collected a large amount of data on designing evolutionary algorithms, which captures rich knowledge in evolutionary computation. However, this data is often discarded or not further investigated in the literature. This includes solutions of different features to inform or drive the evolution/optimisation, data on evolutionary algorithms of different settings and different operators/heuristics, and data on the search space or fitness evaluation. This provides an excellent new problem domain for the machine learning community to enhance evolutionary computation.

Variants of VRP provide an ideal testbed to enable performance comparison of machine learning-assisted evolutionary computation. Fostering, reusing, and benchmarking the rich knowledge building ML4VRP remains a challenge for researchers across disciplines, however, it is highly rewarding to further advances in human-designed evolutionary computation.

Following the success of the previous competitions at GECCO 2023, GECCO 2024 and driven by continued community interest and emerging research developments, we are launching the competition at GECCO 2026, proposing two tracks in VRP:
- CVRP concerns the benchmark VRP problem, a simplified scenario, and the most basic model.
- VRPTW concerns VRP with time windows, which are derived from real-world scenarios.

Abstract Submission

The competition allows 2-page contributions to the GECCO Companion to present short descriptions of the competition entry, focusing on algorithmic design, strengths and limitations. The 2-page abstract paper will require at least one author to register at the conference as a presenter. It is important to mention that these 2-page abstracts ARE NOT APC Eligible (no publication fee has to be paid by the authors) under the current ACM Open publishing guidelines. The following dates are relevant for these submissions:

  • Submission opening: April 1, 2026
  • Submission deadline: April 21, 2026
  • Notification: April 28, 2026
  • Camera-ready: May 5, 2026
  • Author's mandatory registration: May 11, 2026


Organizers

Rong Qu

Prof. Rong Qu is a Professor at the University of Nottingham. Her main research interests include the modelling and optimisation of combinatorial optimisation problems using evolutionary computation, integrated with operational research and artificial intelligence. Prof. Qu is an Associate Editor at five international journals. She has been awarded the 2022 Leverhulme Senior Research Fellowship by The Royal Society.


Weiyao Meng

Weiyao Meng is a Research Fellow at the University of Nottingham Business School. Her main research focuses on automated algorithm design and data-driven decision-making utilising data science, machine learning, and optimisation algorithms. She holds a PhD in Computer Science from the University of Nottingham and has contributed to projects spanning automated algorithm design, industry-focused routing technologies, consumer behaviour analytics, and public health data science. Weiyao serves as the Publicity Chair for IEEE WCCI-CEC 2026 and as a reviewer for leading journals, including IEEE Computational Intelligence Magazine, IEEE Transactions on Evolutionary Computation, Engineering Applications of Artificial Intelligence, and Journal of the Operational Research Society. She is also a member of the IEEE Task Force on Automated Algorithm Design, Configuration and Selection, and the IEEE Task Force on Evolutionary Scheduling and Combinatorial Optimisation.


Isaac Triguero

Isaac Triguero received his M.Sc. and Ph.D. degrees in Computer Science from the University of Granada, Granada, Spain, in 2009 and 2014, respectively. He is a currently enjoying a Distinguished Senior Research Fellowship at the University of Granada, taking a teaching break from his position as an Associate Professor of Data Science at the University of Nottingham. His work is mostly concerned with the research of novel methodologies for big data analytics. Dr Triguero has published more than 90 international publications in the fields of Large-Scale data analytics, Machine Learning and Optimisation (H-index=34 and more than 5300 citations on Google Scholar). He is a Section Editor-in-Chief of the Machine Learning and Knowledge Extraction journal, and an associate editor of the Neurocomputing journal, and the IEEE Access journal. He has acted as Program Co-Chair of the IEEE Conference on Smart Data (2016), the IEEE Conference on Big Data Science and Engineering (2017), and the IEEE International Congress on Big Data (2018). Dr Triguero is currently leading a Knowledge Transfer Partnership project funded by Innovative UK and Unilever that investigates interpretable machine learning models for sustainable business operations, as well as two research contracts with Fullstep Networks S.A. and Arcelor Mittal S.A.


Mustafa MISIR

His research focus is automated algorithm design (machine learning and algorithm design), data science and operations research. His teaching interest is computer science while being involved with a variety of interdisciplinary courses, and he is concerned with industrial engineering and operations research besides computer engineering. He is particularly keen to teach courses on algorithms, data structures, programming, and machine learning/artificial intelligence.
He has received prestigious academic awards and published more than 40 papers in well-known international conferences/journals such as Artificial Intelligence (Elsevier) and IEEE Transactions on Cybernetics. He is an active participant of the IEEE Computational Intelligence Society as a technical committee member while contributing to academia in the program committee of a diverse group of conferences such as AAAI and GECCO. In the meantime, he is carrying out reviewing duties for about 30 international journals along with editorial responsibilities.
Misir has a B.Sc. and M.Sc. in computer engineering from Yeditepe University, Turkey, and a Ph.D. in computer science from KU Leuven, Belgium. Before joining Duke Kunshan, he was a faculty member in computer engineering in addition to being the department chair and vice dean of engineering at Istinye University, Turkey, as a national re-integration grant holder. He previously worked as a postdoctoral researcher (Marie Curie Fellow) at INRIA Saclay - Université Paris Sud XI / Université Paris-Saclay in France before taking postdoctoral positions at Singapore Management University and the University of Freiburg in Germany. He was also a visiting researcher at the University of Zurich and Universitat Politècnica de Catalunya / BarcelonaTech, Spain. He then moved to the Nanjing University of Aeronautics and Astronautics as a faculty member in the College of Computer Science and Technology.