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Open Source Software for Evolutionary Computation

Webpage: https://evooss.heuristiclab.com

Description

Evolutionary computation (EC) methods are applied in many different domains. Therefore, soundly engineered, reusable, flexible, user-friendly, interoperable, and open software for EC is needed more than ever to bridge the gap between theoretical research and practical application. However, due to the heterogeneity of application domains and the large number of EC methods, the development of such software is both, time consuming and complex. Consequently, many EC researchers implement custom, highly specialized, closed source and often throw-away software which focuses on a specific research question and is used only once to produce results for the next paper. It is not yet standard in the EC community that the software used to produce the presented results is also made available as open source software in each publication, let alone that this software is also engineered in such a way that others can easily base their research work on it or apply it in practice. This significantly hinders the comparability and reproducibility of research results in the field.

This workshop promotes the development and dissemination of open source software for evolutionary computation and provides a platform for EC researchers to present their latest open source software libraries, frameworks, and tools for the development, analysis, and application of evolutionary algorithms.

Please note that submissions to this workshop will only be accepted if they describe open source software for EC that has already been released and is publically available. The URL to the source code repository must be included in the paper. Therefore, contributions to this workshop have not to be submitted in anonymized form, as the identity of the authors is usually very easy to determine from the repository.

Submission format

Extended Abstracts (up to 4 pages): Are not eligible for APC - no fee paid by the authors for ACM Open Access. An Extended Abstract provides a summary of a work-in-progress, typically just enough for readers to understand the idea, scope, and potential impact. It often lacks full methodology, detailed results, or extensive references.

Important dates

  • Submission opening: February 2, 2026
  • Submission deadline: March 27, 2026 April 03, 2026
  • Notification: April 24, 2026
  • Camera-ready: May 5, 2026
  • Author's mandatory registration: May 11, 2026

ACMs new Open Access publishing model for 2026 ACM Conferences

Starting January 1, 2026, ACM will fully transition to Open Access. All ACM publications, including those from ACM-sponsored conferences, will be 100% Open Access. Authors will have two primary options for publishing Open Access articles with ACM: the ACM Open institutional model or by paying Article Processing Charges (APCs). With over 2,600 institutions already part of ACM Open, the majority of ACM-sponsored conference papers will not require APCs from authors or conferences (currently, around 76%).

Authors from institutions not participating in ACM Open will need to pay an APC to publish their papers, unless they qualify for a financial waiver. To find out whether an APC applies to your article, please consult the list of participating institutions in ACM Open and review the APC Waivers and Discounts Policy. Keep in mind that waivers are rare and are granted based on specific criteria set by ACM.

Understanding that this change could present financial challenges, ACM has approved a temporary subsidy for 2026 to ease the transition and allow more time for institutions to join ACM Open. The subsidy will offer:

  • $250 APC for ACM/SIG members
  • $350 for non-members

This represents a 65% discount, funded directly by ACM. Authors are encouraged to help advocate for their institutions to join ACM Open during this transition period.

This temporary subsidized pricing will apply to all conferences scheduled for 2026.

Additionally, SIGEVO will provide an additional subsidy of $125 to papers accepted to GECCO 2026 (and only for 2026) that are subject to APCs. This will make the final amounts to be paid:

  • $125 (USD) for SIGEVO members
  • $225 (USD) for non-members

It is IMPORTANT to mention that both forms of subsidy (by ACM and by SIGVO) only apply to GECCO 2026. Moreover, it is still to be determined how the SIGEVO subsidy will be implemented, either directly to the APC or in other forms.

Finally, we note that APC charges apply to accepted Full Papers, but Abstracts (1-2 pages), Extended Abstracts (1-4 pages) and Tutorials ARE NOT APC Eligible; i.e., an APC will not have to be paid for these types of contributions.

ACM Authorship and Peer Review Policies on Generative AI

GECCO follows the official ACM policies on authorship and peer review, including the use of generative AI tools.

Under ACM's Authorship policy, generative AI tools and technologies cannot be listed as authors of an ACM published Work. The use of generative AI tools and technologies for assistance must be fully disclosed in the manuscript's Acknowledgments section. Authors are fully accountable for the originality, accuracy, and integrity of all submitted material.

In accordance with ACM's Peer Review policy, reviewers must not upload or share submitted manuscripts or review materials with generative AI systems. Reviewers may use generative AI or tools with the sole purpose of improving the quality and readability of reviewer reports for the author.

ACM is actively developing tools to help identify improper AI use in submissions, and GECCO may employ available detection methods. Submissions found to violate ACM policies may be rejected.


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Organizers

Stefan Wagner

Stefan Wagner received his MSc in computer science in 2004 and his PhD in technical sciences in 2009, both from Johannes Kepler University Linz, Austria. From 2005 to 2009 he worked as associate professor for software project engineering and since 2009 as full professor for complex software systems at the Campus Hagenberg of the University of Applied Sciences Upper Austria. From 2011 to 2018 he was also CEO of the FH OÖ IT GmbH, which is the IT service provider of the University of Applied Sciences Upper Austria. Dr. Wagner is one of the founders of the research group Heuristic and Evolutionary Algorithms Laboratory (HEAL) and is project manager and head architect of the open-source optimization environment HeuristicLab. He works as project manager and key researcher in several R&D projects on production and logistics optimization and his research interests are in the area of combinatorial optimization, evolutionary algorithms, computational intelligence, and parallel and distributed computing.

 
Michael Affenzeller

Michael Affenzeller has published several papers, journal articles and books dealing with theoretical and practical aspects of evolutionary computation, genetic algorithms, and meta-heuristics in general. In 2001 he received his PhD in engineering sciences and in 2004 he received his habilitation in applied systems engineering, both from the Johannes Kepler University Linz, Austria. Michael Affenzeller is professor at the University of Applied Sciences Upper Austria, Campus Hagenberg, head of the research group Heuristic and Evolutionary Algorithms Laboratory (HEAL), head of the Master degree program Software Engineering, vice-dean for research and development, and scientific director of the Softwarepark Hagenberg.