CoSPLib - A Benchmark Library for Conference Scheduling Problems

Conference scheduling problems require the generation of schedules for conferences by considering multiple constraints to offer the best possible experience to participants. Previous studies have been published in the literature, however, the comparison and evaluation of the developed methods is challenging, as these methods have been designed to address rather specific requirements of the conferences being studied per se. In this work, we attempt to bridge this gap by making benchmark data publicly available to researchers. We also present a selection hyper-heuristic algorithm to solve the benchmark instances and provide computational results. We aim to raise awareness of the under-studied conference scheduling problem, and to encourage researchers to contribute to the benchmark dataset with new instances, constraints, and solving methods.

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Publication Details

Journal
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Published
2025-07-14
DOI
https://doi.org/10.1145/3712255.3726570
Primary Topic
Scheduling and Timetabling Solutions
Type
article
Field-Weighted Citation Impact
0.00
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article

CoSPLib - A Benchmark Library for Conference Scheduling Problems

Peter Jacko, Ahmed Kheiri, Yaroslav Pylyavskyy
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Scheduling and Timetabling Solutions
article

CoSPLib - A Benchmark Library for Conference Scheduling Problems

Peter Jacko, Ahmed Kheiri, Yaroslav Pylyavskyy
article en

Abstract

Conference scheduling problems require the generation of schedules for conferences by considering multiple constraints to offer the best possible experience to participants. Previous studies have been published in the literature, however, the comparison and evaluation of the developed methods is challenging, as these methods have been designed to address rather specific requirements of the conferences being studied per se. In this work, we attempt to bridge this gap by making benchmark data publicly available to researchers. We also present a selection hyper-heuristic algorithm to solve the benchmark instances and provide computational results. We aim to raise awareness of the under-studied conference scheduling problem, and to encourage researchers to contribute to the benchmark dataset with new instances, constraints, and solving methods.

Proceedings of the Genetic and Evolutionary Computation Conference Companion
University of Manchester (GB), Berry & Associates (United States) (US), Lancaster University (GB)
Openalex Percentile: Top 42%
Scheduling and Timetabling Solutions
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CoSPLib - A Benchmark Library for Conference Scheduling Problems — Peter Jacko, Ahmed Kheiri, et al. · Proceedings of the Genetic and Evolutionary Computation Conference Companion (2025) | TGRS Research Map | TGRS