Title :

An adaptive evolution control based on confident regions for surrogate-assisted optimization

Author(s) :

Briffoteaux, Guillaume [Auteur]
Institut de Mathématiques [Mons]
Optimisation de grande taille et calcul large échelle [BONUS]
Melab, Nouredine [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Mezmaz, Mohand [Auteur]
Institut de Mathématiques [Mons]
Tuyttens, Daniel [Auteur]
Institut de Mathématiques [Mons]

Conference title :

HPCS 2018 - International Conference on High Performance Computing & Simulation

City :

Orléans

Country :

France

Start date of the conference :

2018-07-16

English keyword(s) :

machine learning
evolution control
Surrogate-modeling
multi-objective optimization
direct fitness replacement

HAL domain(s) :

Mathématiques [math]/Optimisation et contrôle [math.OC]

English abstract : [en]

In simulation-based optimization the objective function is often computationally expensive for many optimization problems. Surrogate-assisted optimization is therefore a major approach to efficiently solve them. One of the ...
Show more >In simulation-based optimization the objective function is often computationally expensive for many optimization problems. Surrogate-assisted optimization is therefore a major approach to efficiently solve them. One of the major issues of this approach is how to integrate the approximate models (surrogates or metamodels) in the optimization process. The challenge is to find the best trade-off between the quality (in terms of precision) of the provided solutions and the efficiency (in terms of execution time) of the resolution. In this paper, we investigate the evolution control that alternates between the simulator and the surrogate within the optimization process. We propose an adaptive evolution control mechanism based on the distance-based concept of confident regions. The approach has been integrated into an ANN-assisted NSGA-2 and experimented using the ZDT4 multi-modal benchmark function. The reported results show that the proposed approach outperforms two other existing ones.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL