A Template for Designing Single-Solution Hybrid Metaheuristics

Abstract : Single-solution metaheuristics are among the earliest and most successful metaheuristics, with many variants appearing in the literature. Even among the most popular variants, there is a large degree of overlap in terms of actual behavior. Moreover, in the case of hybrids of different metaheuristics, traditional names do not actually re ect how the hybrids are composed. In this paper, we discuss a template for singlesolution hybrid metaheuristics. Our template builds upon the Paradiseo-MO framework, but restricts itself to a predefined structure based on iterated local search (ILS). The exibility is given by generalizing the components of ILS (perturbation, local search and acceptance criterion) in order to incorporate components from other metaheuristics. We give precise definitions of these components within the context of our proposed template. The template proposed is exible enough to reproduce many classical single-solution metaheuristics and hybrids thereof, while at the same time being sufficiently concrete to generate code from a grammar description in order to support automatic design of algorithms. We give examples of three IG-VNS hybrids that can be instantiated from the proposed template.
Type de document :
Communication dans un congrès
Christian Igel. Genetic and evolutionary computation companion, GECCO Comp'14, 2014, Vancouver, Canada. ACM, 2014, Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion, GECCO Comp'14
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https://hal.inria.fr/hal-01094686
Contributeur : Marie-Eléonore Kessaci <>
Soumis le : vendredi 12 décembre 2014 - 17:23:20
Dernière modification le : jeudi 11 janvier 2018 - 06:22:13

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  • HAL Id : hal-01094686, version 1

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Manuel López-Ibáñez, Franco Mascia, Marie-Eléonore Marmion, Thomas Stützle. A Template for Designing Single-Solution Hybrid Metaheuristics. Christian Igel. Genetic and evolutionary computation companion, GECCO Comp'14, 2014, Vancouver, Canada. ACM, 2014, Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion, GECCO Comp'14. 〈hal-01094686〉

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