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RWA - Real World Applications

Description

The Real-World Applications (RWA) track welcomes rigorous experimental, computational and/or applied advances in evolutionary computation (EC) in any discipline devoted to the study of real-world problems. The RWA track covers also real-world problems arising in creative arts, including design, games, and music (having been merged with the former track DETA - Digital Entertainment Technologies and Arts), and search-based software engineering problems (the SBSE track having been discontinued). The aim is to bring together contributions from the diverse application domains into a single event.

Please note that, from 2025, the track will handle strictly new real-world applications. That is, applications that are newly modelled and solved with evolutionary algorithms. In other words, we will not consider articles that use previously existing, publicly available real-world benchmark problems. If you are using existing/published real-world benchmarks, you can submit to other GECCO tracks that are relevant to your algorithmic contributions.

The focus is on applications including but not limited to:

  • Papers that present novel developments of EC, grounded in real-world problems.
  • Papers that present new applications of EC to real-world problems.
  • Papers that analyse the features of real-world problems, as a basis for designing EC solutions.
  • Papers that would fall into the DETA domain, such as ones focussing on aesthetic measurement and control, biologically-inspired creativity, interactive environments and games, composition, synthesis and generative arts.
  • Papers on search-based software engineering applications, such as automatic program repair, genetic improvement, software testing, requirements analysis, and project management.


All contributions should be original research papers demonstrating the relevance and applicability of EC within a real-world problem. Papers covering multiple disciplines are welcome; we encourage the authors of such papers to write and present them in a way that allows researchers from other fields to grasp the main results, techniques, and their potential applications. Papers on novel EC research problems and novel application domains of the arts, music, and games are especially encouraged.

Scope

The real-world applications track is open to all domains and all industries.


Track Chairs

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Alexander Brownlee

University of Stirling | webpage

Alexander (Sandy) Brownlee is a Senior Lecturer in the Division of Computing Science and Mathematics at the University of Stirling, where he leads the Data Science and Intelligent Systems research group. His main topics of interest are in search-based optimisation methods and machine learning, with a focus on decision support tools, and applications in civil engineering, transportation and software engineering. He has published over 80 peer-reviewed papers on these topics. He has worked with several leading businesses including BT, KLM, and IES on industrial applications of optimisation and machine learning. He serves as a reviewer for several journals and conferences in evolutionary computation, civil engineering and transportation, and is currently an Editorial Board member for the journal Complex And Intelligent Systems. He has been an organiser of several workshops and tutorials at GECCO, CEC and PPSN on genetic improvement of software.

Roman Kalkreuth

RWTH Aachen University

Roman Kalkreuth is currently an assistant professor at the Chair of Artificial Intelligence Methodology of Professor Holger Hoos which belongs to RWTH Aachen University in Germany. Primarily, his research focuses on the analysis and development of algorithms for graph-based genetic programming. From 2015 until 2022, he was a research associate of the Computational Intelligence Research Group of Professor Guenter Rudolph at TU Dortmund University (Germany). Roman Kalkreuth defended his PhD thesis in July 2021 and then took up a postdoctoral researcher position within Professor Rudolph’s group. From October 2022 to June 2023, he worked in the Natural Computing Research Group of Professor Dr. Thomas Bäck at the Leiden Institute of Advanced Computer Science, which is part of Leiden University. He joined Laboratoire d’Informatique de Paris 6 (LIP6) of Sorbonne University in Paris as a postdoctoral researcher under supervision of Carola Doerr from June 2023 until March 2024. He then took up an assistant professor position at RWTH Aachen University, which started in April 2024.

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Yi Mei

School of Engineering and Computer Science, Victoria University of Wellington, New Zealand | webpage

Yi Mei is an Associate Professor/Reader at the School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand. His research interests include evolutionary computation and machine learning for combinatorial optimisation, hyper-heuristics, genetic programming, automatic algorithm design, and explainable AI. Yi has more than 250 fully refereed publications, including the top journals in EC and Operations Research (OR) such as IEEE TEVC, IEEE Transactions on Cybernetics, European Journal of Operational Research, ACM Transactions on Mathematical Software, and top EC conferences (GECCO). He won an IEEE Transactions on Evolutionary Computation Outstanding Paper Award 2017, GECCO Best Paper Awards in 2022, 2023 and 2024, the EuroGP Best Paper Award 2022, and a GECCO Humies Silver Award. He is the Chair of IEEE CIS Travel Grant subcommittee, Chair of IEEE Taskforce on Evolutionary Scheduling and Combinatorial Optimisation, and Chair of IEEE New Zealand Central Section. He is an Associate Editor/Editorial Board Member of 7 international journals, including the IEEE Transactions on Evolutionary Computation, IEEE Transactions on Artificial Intelligence, and Journal of Scheduling. He is a Fellow of Engineering New Zealand and an IEEE Senior Member.