Efficient Scheduling of GECCO Conferences using Hyper-heuristic Algorithms

Ahmed Kheiri*, Yaroslav Pylyavskyy, Peter Jacko

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationGECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion
PublisherAssociation for Computing Machinery
Pages1732-1737
Number of pages6
ISBN (Electronic)9798400704956
DOIs
Publication statusPublished - 14 Jul 2024
Event2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion - Melbourne, Australia
Duration: 14 Jul 202418 Jul 2024

Publication series

NameGECCO 2024 Companion - Proceedings of the 2024 Genetic and Evolutionary Computation Conference Companion

Conference

Conference2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion
Country/TerritoryAustralia
CityMelbourne
Period14/07/2418/07/24

Keywords

  • conference scheduling problem
  • hyper-heuristic
  • optimisation

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