@inproceedings{ec2600f17f3d450cbb6f7f0c32e40741,
title = "Efficient Scheduling of GECCO Conferences using Hyper-heuristic Algorithms",
abstract = "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.",
keywords = "conference scheduling problem, hyper-heuristic, optimisation",
author = "Ahmed Kheiri and Yaroslav Pylyavskyy and Peter Jacko",
note = "Publisher Copyright: {\textcopyright} 2024 Copyright held by the owner/author(s).; 2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion ; Conference date: 14-07-2024 Through 18-07-2024",
year = "2024",
month = jul,
day = "14",
doi = "10.1145/3638530.3664186",
language = "English",
series = "GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion",
publisher = "Association for Computing Machinery",
pages = "1732--1737",
booktitle = "GECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion",
address = "United States",
}