21-26 June 2026 | MEEC Maastricht, Netherlands
In recent years, algorithm configuration and selection have become critical components in advancing the performance of optimization, machine learning, and AI systems. Traditionally, algorithms rely on static, one-size-fits-all configurations, which often fail to adapt to diverse problem landscapes or dynamic environments. This limitation has motivated research into dynamic algorithm configuration (DAC), where parameters are dynamically adjusted over time based on problem’s characteristics, or dynamic algorithm selection, where the algorithms chosen for a given problem or even for an instance change over time.
This special session aims to provide an environment for researchers and practitioners to discuss the latest advances, methodologies, and applications in dynamic automated algorithm configuration and algorithm selection. The session will focus on the design, analysis, and deployment of adaptive systems capable of adjusting their strategies during execution. By bringing together contributions from optimization, machine learning, operations research, and real-world application domains, we aim to foster interdisciplinary discussions and identify open challenges and future research directions.
Keywords:
Dynamic algorithm configuration, dynamic algorithm selection, parameter control, self-adapting algorithms
This session will serve as a venue for both theoretical contributions and applied research, encouraging the exchange of ideas between academia and industry.
Topics of interest tackle dynamic automated algorithm configuration and algorithm selection. They can be, but are not limited to:
Dynamic algorithm configuration
Online and dynamic algorithm selection
Parameter control and adaptive mechanisms in optimization methods
Data-driven approaches for configuration and selection
Reactive search methods and self-adaptive heuristics
Benchmarks, performance evaluation, and explainability in dynamic configuration
Applications in logistics, scheduling, energy systems, AI planning, and beyond
Important Dates
Paper Submission Deadline: January 31, 2026
Paper Acceptance Notification: March 15, 2026
Final Paper Submission: April 15, 2026
Event's Date: June 21 – 26, 2026
Submission
All submissions must conform to the official guidelines provided on the WCCI 2026 website. The key requirements are summarized below:
Special Session papers are subject to the same rules and review criteria as regular conference papers.
All papers must be submitted through the IEEE WCCI 2026 online submission system.
Submissions must be complete manuscripts not exceeding eight (8) pages, according to the IEEE two-column conference proceedings format.
WCCI operates under a double-blind peer-review policy. Authors must ensure that their manuscripts are fully anonymized before submission.
Accepted contributions will appear in the IEEE Xplore conference proceedings.
During the submission process, authors must explicitly indicate that their paper is intended for the WCCI/CEC Special Session "Dynamic Algorithm Configuration and Selection".
Organizers
Affiliation: (1) LIP6, CNRS, Sorbonne Université, (2) Khemis Miliana University
Email: imene.ait-abderrahim@lip6.fr / i.aitabderrahim@univ-dbkm.dz
Website: https://lip6.fr/Imene.Ait-Abderrahim
Bio: Imène Ait Abderrahim is currently a Postdoc researcher at LIP6, Sorbonne University, France. She holds a PhD in Computer Science from Oran 1 University, Algeria, in 2020. After that, she worked as an Associate professor for four years at Khemis Meliana University until 2025. Her research area is operations research, combinatorial optimization, metaheuristics, and automatic algorithm configuration.
Affiliation: University of St Andrews
Email: nttd@st-andrews.ac.uk
Website: https://ndangtt.github.io/
Bio: Nguyen Dang is a Lecturer (Assistant Professor) at the University of St Andrews. She received a PhD degree from KU Leuven in 2018. Her research interests include automated algorithm configuration, automated algorithm selection, as well as their applications in both black-box optimisation and constraint programming. Her joint work in automated algorithm configuration has received best paper awards at GECCO 2017, GECCO 2022, and GECCO 2025, and a runner-up for best paper award at FOGA 2023.
Affiliation: Université Libre de Bruxelles (ULB)
Email: stuetzle@ulb.ac.be
Website: https://iridia.ulb.ac.be/~stuetzle/
Bio: He is a Research Director of the Belgian F.R.S.-FNRS working in the Institut de Recherches Interdisciplinaires et de Développements en Intelligence Artificielle (IRIDIA), Université libre de Bruxelles, Brussels, Belgium. He is author of the two books: Stochastic Local Search: Foundations and Applications (Morgan Kaufmann) and Ant Colony Optimization (MIT Press). He has published extensively in the wider area of metaheuristics (more than 250 peer-reviewed articles in journals, conference proceedings, or edited books). His research interests range from stochastic local search (SLS) algorithms, large scale experimental studies, automated design of algorithms, to SLS algorithms engineering.