hal-00713415, version 1
Alternative Restart Strategies for CMA-ES
Ilya Loshchilov
1Marc Schoenauer
1, 2Michèle Sebag
1, 3
Parallel Problem Solving From Nature (2012)
Résumé : This paper focuses on the restart strategy of CMA-ES on multi-modal functions. A first alternative strategy proceeds by decreasing the initial step-size of the mutation while doubling the population size at each restart. A second strategy adaptively allocates the computational budget among the restart settings in the BIPOP scheme. Both restart strategies are validated on the BBOB benchmark; their generality is also demonstrated on an independent real-world problem suite related to spacecraft trajectory optimization.
- 1 : TAO (INRIA Saclay - Ile de France)
- INRIA – CNRS : UMR8623 – Université Paris XI - Paris Sud
- 2 : Microsoft Research - Inria Joint Centre (MSR - INRIA)
- INRIA – Microsoft – Microsoft Research Laboratory Cambridge
- 3 : Laboratoire de Recherche en Informatique (LRI)
- CNRS : UMR8623 – Université Paris XI - Paris Sud
- Domaine : Informatique/Intelligence artificielle
- Mots-clés : evolutionary computation – multi-modal optimization – cma-es – restart strategies
- hal-00713415, version 1
- http://hal.inria.fr/hal-00713415
- oai:hal.inria.fr:hal-00713415
- Contributeur : Loshchilov Ilya
- Soumis le : Dimanche 1 Juillet 2012, 06:46:07
- Dernière modification le : Dimanche 1 Juillet 2012, 15:50:26






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