1. the complete title of one (or more) paper(s) published in the open literature describing the work that the author claims describes a human-competitive result; Efficient Scheduling of GECCO Conferences using Hyper-heuristic Algorithms 2. the name, complete physical mailing address, e-mail address, and phone number of EACH author of EACH paper(s); Ahmed Kheiri, Lancaster University Management School, Department of Management Science, Lancaster, LA1 4YX, United Kingdom, a.kheiri@lancaster.ac.uk, T: +44 (0)1524 593117 Yaroslav Pylyavskyy, Lancaster University Management School, Department of Management Science, Lancaster, LA1 4YX, United Kingdom, y.pylyavskyy1@lancaster.ac.uk Peter Jacko, Lancaster University Management School, Department of Management Science, Lancaster, LA1 4YX, United Kingdom, p.jacko@lancaster.ac.uk & Berry Consultants, 5 East Saint Helen Street, Abingdon, OX14 5EG, United Kingdom 3. the name of the corresponding author (i.e., the author to whom notices will be sent concerning the competition); Ahmed Kheiri 4. the abstract of the paper(s); We propose the development of a conference scheduler tailored specifically for the Genetic and Evolutionary Computation Conference (GECCO). Our proposed flexible approach allows GECCO organisers to optimise conference schedules according to their specific needs and available resources. Using hyper-heuristic methods, our scheduler generates optimised solutions for in-person and hybrid GECCO conferences. We validate our method using data from GECCO2019 and demonstrate its effectiveness by successfully creating schedules for GECCO conferences from 2020 onwards. 5. a list containing one or more of the eight letters (A, B, C, D, E, F, G, or H) that correspond to the criteria (see above) that the author claims that the work satisfies; (D) The result is publishable in its own right as a new scientific result independent of the fact that the result was mechanically created. (F) The result is equal to or better than a result that was considered an achievement in its field at the time it was first discovered. (G) The result solves a problem of indisputable difficulty in its field. 6. a statement stating why the result satisfies the criteria that the contestant claims (see examples of statements of human-competitiveness as a guide to aid in constructing this part of the submission); (D) The result is publishable in its own right as a new scientific result independent of the fact that the result was mechanically created. The development of the conference scheduler using hyper-heuristic represents a novel and impactful application in the field of computational optimisation. This scheduler addresses the complex, real-world problem of efficiently scheduling conferences with numerous sessions and varying formats, including in-person and hybrid conferences. Its validation using data from GECCO2019 and successful application to subsequent conferences provide strong empirical evidence of its effectiveness. The research significantly contributes to conference management by demonstrating the application of hyper-heuristics on scheduling conferences in an autonomous, effortless and fully automated manner. Furthermore, it advances the broader field of computational optimisation, providing a case study that can inspire further innovations in similar contexts. (F) The result is equal to or better than a result that was considered an achievement in its field at the time it was first discovered. The conference scheduler has proven to be significantly more effective than the manually constructed schedule of GECCO2019. A detailed comparison showed that our solver identified 14 constraint violations compared to 25 in the manual schedule. The solver had fewer violations in key areas: it violated rooms allocated per track constraints twice versus six times manually, and room usage constraints twice versus four times manually. Additionally, consecutive track scheduling constraints were violated 11 times by the solver, compared to 13 times in the manual solution. It is important to note that neither solution was evaluated based on participants' preferences, as we lacked access to this information. Additionally, GECCO2019 was an in-person event and it did not exhibit the challenges associated with scheduling hybrid conferences. These results clearly demonstrate that the solver outperforms manual conference scheduling, producing better outcomes with fewer violations and significantly less effort. Its effectiveness led to its adoption for subsequent conferences, including GECCO2020 through GECCO2023, and it will also be used to schedule GECCO2024. (G) The result solves a problem of indisputable difficulty in its field. The conference scheduler tackles the challenging problem of conference scheduling, which has been proved to be NP-Hard, and takes into consideration multiple constraints. Scheduling a conference is an arduous, time-consuming, and error-prone task involving numerous constraints and requirements such as scheduling all presentations, ensuring no conflicts, adhering to session limits, and accommodating individual availability, particularly in hybrid and online formats where time zones must be considered. Additional complexities include room accessibility, track-specific session restrictions, appropriate room assignments based on expected attendance, avoiding parallel scheduling of the same tracks, and not scheduling similar tracks simultaneously. Sometimes specific rooms are unavailable during certain sessions, and it is crucial to minimise the number of rooms per track for convenience. Moreover, attendees' preferences must also be accommodated to avoid conflicts, some presentations must be scheduled in specific sequences and others require multiple time slots to be completely scheduled. Furthermore, scheduling tracks consecutively to maintain a cohesive schedule is essential. Our hyper-heuristic solver effectively addresses these complexities, as shown by its superior performance over the manual GECCO2019 schedule. This validation and the solver's consistent use from GECCO2020 through GECCO2023 demonstrate its capability to handle the numerous complexities arising during conference scheduling. Additionally, the same algorithm has been tested on solving scheduling problems for other conferences, such as OR60 and N2OR. 7. a full citation of the paper (that is, author names; title, publication date; name of journal, conference, or book in which article appeared; name of editors, if applicable, of the journal or edited book; publisher name; publisher city; page numbers, if applicable); Ahmed Kheiri, Yaroslav Pylyavskyy, and Peter Jacko. 2024. Efficient Scheduling of GECCO Conferences using Hyper-heuristic Algorithms. In Genetic and Evolutionary Computation Conference (GECCO '24 Companion), July 14–18, 2024, Melbourne, VIC, Australia. ACM, New York, NY, USA. https://doi.org/10.1145/3638530.3664186 8. a statement either that "any prize money, if any, is to be divided equally among the co-authors" OR a specific percentage breakdown as to how the prize money, if any, is to be divided among the co-authors; To be divided equally among the co-authors. 9. a statement stating why the authors expect that their entry would be the "best"; We believe our entry is the "best" for the following reasons: 1) Novel Application of Hyper-Heuristics: The use of hyper-heuristics in scheduling, particularly tailored for a specific and complex conference like GECCO, represents a novel application. While hyper-heuristics have been studied in various optimisation problems, their specific adaptation and implementation for conference scheduling with the flexibility to handle both in-person and hybrid formats is a significant innovation. 2) Addressing a Real-World Problem: The conference scheduler addresses a practical problem within the academic community. Conferences like GECCO require efficient scheduling to offer the best possible experience for participants considering multiple constraints. Our solution is also suitable for other conferences in optimising their schedules, which provides substantial value, making the work highly relevant and impactful. 3) Validation and Empirical Evidence: The validation of the scheduler using real data from GECCO2019 and its successful application to subsequent conferences from 2020 onwards provides strong empirical evidence of its effectiveness. This empirical validation is critical within the field of genetic and evolutionary algorithms development, demonstrating that the proposed hyper-heuristic works in practice, not just in theory. 4) Contribution to the Field of Computational Optimisation: Our research advances the field of computational optimisation by presenting a case study of hyper-heuristic application. This can serve as a foundation for future research, exploring how hyper-heuristics can be refined or adapted for other complex scheduling problems. 10. An indication of the general type of genetic or evolutionary computation used; ECOM (Evolutionary Combinatorial Optimisation and Metaheuristics) 11. The date of publication of each paper. If the date of publication is not on or before the deadline for submission, but instead, the paper has been unconditionally accepted for publication and is "in press" by the deadline for this competition, the entry must include a copy of the documentation establishing that the paper meets the "in press" requirement; The paper has been accepted for the current year's GECCO conference.