Because of the breadth of topics covered, GECCO conferences are organised in multiple parallel tracks, in order to create time for presentation even after peer-review has reduced the number of papers from those initially submitted. The slogan "One Conference: Many Mini-Conferences" appears on the website • BBSR - Benchmarking, Benchmarks, Software and Reproducibility • CS -
Complex Systems • ECOM - Evolutionary
Combinational Optimisation and
Metaheuristics • EML - Evolutionary
Machine Learning • EMO - Evolutionary
Multiobjective Optimisation • ENUM - Evolutionary Numerical Optimisation • GA -
Genetic Algorithms • GECH - General Evolutionary Computation and Hybrids • GP -
Genetic Programming • L4EC - Learning for Evolutionary Computation • NE -
Neuroevolution • RWA - Real World Applications • SI -
Swarm Intelligence • THEORY - Theory
Keynote speakers Each GECCO conference invites speakers with a considerable record in the field of
evolutionary computation or in other aspects of public engagement to give keynote presentations. For example, at GECCO 2024 they were
Toby Walsh,
Suzie Sheehy and
Una-May O'Reilly.
Women+@GECCO Since 2013 there has been a workshop held at each GECCO conference to support women in
evolutionary computation. It includes an interactive poster session.
Workshops The workshop slots of GECCO conferences allows time to be devoted to subjects that might not be addressed fully in the main conference. Workshop organisers identify how their slot will be used and often issue a call for papers, separate from the main call for papers for the conference. In addition there is a Student Workshop allowing students of
evolutionary computation early in their careers to engage in the conference. GECCO 2023 in Lisbon included 23 workshops, many of which were successors to ones held in earlier years.
Tutorials Since
evolutionary computation is very much about the implementation of novel solutions using
software engineering techniques (with the exception of the theoretical aspect of the field) the tutorials section of a GECCO conference allows attendees to be introduced to areas of the field that they are not so familiar with. GECCO 2022 in Boston included 38 tutorials. Despite the mention of
software engineering above some of these tutorials covered somewhat theoretical topics: A Gentle Introduction to Theory (for Non-Theoreticians) or Theory and Practice of Population Diversity in Evolutionary Computation. Tutorials and Workshops have in recent years taken place prior to the main conference, see the program of GECCO 2025 for an example. Tutorial abstracts and workshop proceedings are published in the companion volume. shows where HOP papers appear in that year. HOP papers are published in the companion volume. Poster abstracts are published in the companion volume.
Competitions In addition to the Humies contest referred to on the
ACM SIGEVO website and in the
Awards section below, other competitions are organised for GECCO conferences to stimulate solutions using
evolutionary computation and related
algorithms. During the conference time is available for the competitions in parallel with workshops and tutorials. • The SIGEVO Outstanding Contribution Award recognises outstanding contributions in the field of
evolutionary computation over at least 15 years. • The GECCO Best Paper awards are awarded for each
track of a GECCO conference. • The SIGEVO Dissertation Award recognises thesis research within the scope of GECCO conferences carried out in the year prior to a conference. • The SIGEVO Impact Award recognises papers that were published in a GECCO conference ten years earlier, that have been assessed to have had considerable impact on the field of
evolutionary computation. • The SIGEVO Chair Lecture is a lecture sponsored by
ACM SIGEVO given by influential researchers in the field. • The Humies Awards are presented at GECCO conferences for human-competitive results using any form of
genetic or evolutionary computation published in the previous year. They are not sponsored by
ACM SIGEVO but originated through a donation from the computer scientist
John Koza. ==Significance==