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Generalizing the Structure of a University Timetabling Solver for Flexible Automatic Algorithm Configuration

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Title: Generalizing the Structure of a University Timetabling Solver for Flexible Automatic Algorithm Configuration
Authors: Feutrier, Thomas, Veerapen, Nadarajen, Kessaci, Marie-Eléonore
Contributors: Veerapen, Nadarajen
Source: Proceedings of the Genetic and Evolutionary Computation Conference Companion. :555-558
Publisher Information: ACM, 2025.
Publication Year: 2025
Subject Terms: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Local Search, Automatic Algorithm Configuration, [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], Hydrid Metaheuristic, [INFO.INFO-RO] Computer Science [cs]/Operations Research [math.OC], Timetabling
Description: This paper explores how a state-of-the-art hybrid metaheuristic for Curriculum-based Course Timetabling, composed of several algorithmic building blocks, can be deconstructed and reconfigured to produce a better algorithm. In particular, an Iterated Local Search strategy is proposed that allows reordering, chaining and looping together the building blocks, and to configure both the global and local search components. This then gives irace, an automatic configurator, the flexibility to explore configurations instantiating different hybrid metaheuristic configurations that outperform the original method. Since using such a configurator can be seen as a black-box process, we provide a comprehensive analysis that determines which parameters are decisive in obtaining the best configurations, finds relevant associations, and analyses the distribution of crucial parameters. In particular, we find that the best configurations discard the simulated annealing component of the original algorithm, as well as some neighborhood operators. The range of necessary algorithmic mechanisms to achieve the new state-of-the-art performance can therefore be reduced.
Document Type: Article
Conference object
File Description: application/pdf
DOI: 10.1145/3712255.3726683
Access URL: https://hal.science/hal-05207043v1
https://hal.science/hal-05207043v1/document
https://doi.org/10.1145/3712255.3726683
Accession Number: edsair.doi.dedup.....a09c7d7ce2b42e74844502db309eb0d3
Database: OpenAIRE
Description
Abstract:This paper explores how a state-of-the-art hybrid metaheuristic for Curriculum-based Course Timetabling, composed of several algorithmic building blocks, can be deconstructed and reconfigured to produce a better algorithm. In particular, an Iterated Local Search strategy is proposed that allows reordering, chaining and looping together the building blocks, and to configure both the global and local search components. This then gives irace, an automatic configurator, the flexibility to explore configurations instantiating different hybrid metaheuristic configurations that outperform the original method. Since using such a configurator can be seen as a black-box process, we provide a comprehensive analysis that determines which parameters are decisive in obtaining the best configurations, finds relevant associations, and analyses the distribution of crucial parameters. In particular, we find that the best configurations discard the simulated annealing component of the original algorithm, as well as some neighborhood operators. The range of necessary algorithmic mechanisms to achieve the new state-of-the-art performance can therefore be reduced.
DOI:10.1145/3712255.3726683