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, music, and search-based software engineering (having been merged with the former track DETA - Digital Entertainment Technologies and Arts and SBSE tracks). The aim is to bring together contributions from the diverse application domains into a single event.
Please note that 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.
Scope:
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.
Track Chairs
Alexander Brownlee
University of Stirling, UK | webpage
Alexander (Sandy) Brownlee is an Associate Professor 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 85 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 journals Complex And Intelligent Systems and Journal of Scheduling. He has also been an organiser of several workshops and tutorials at GECCO and CEC on genetic improvement of software, and on explainable AI for optimisation.Roman Kalkreuth
RWTH Aachen University, Germany
Roman Kalkreuth is currently an assistant professor at 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 Günter 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.Yi Mei
School of Engineering and Computer Science, Victoria University of Wellington, New Zealand | webpage
Dr. Yi Mei is an Associate Professor at Victoria University of Wellington, New Zealand. His research interests include evolutionary computation for combinatorial optimisation, genetic programming, automatic algorithm design, explainable AI, multi-objective optimisation, transfer/multitask learning and optimisation, and their real-world applications. He has published on top journals in EC and Operations Research (OR) such as IEEE TEVC, IEEE TCYB, EJOR, IEEE Transactions on Services Computing, and ACM Transactions on Mathematical Software. He won an IEEE Transactions on Evolutionary Computation Outstanding Paper Award 2017, GECCO Best Paper Awards in 2022, 2023 and 2024, and the EuroGP Best Paper Award 2022.
He was a GECCO ECOM Track Chair for 2023-2024. He is an Associate Editor of IEEE Transactions on Evolutionary Computation, Computational Intelligence Magazine, IEEE Transactions on Artificial Intelligence, Journal of Scheduling, and an Editorial Board Member/Associate Editor of four other international journals. He is the Chair of the IEEE Taskforce on Evolutionary Scheduling and Combinatorial Optimisation. He is a Fellow of Engineering New Zealand and an IEEE Senior Member.