Titre :

Batch Acquisition for Parallel Bayesian Optimization—Application to Hydro-Energy Storage Systems Scheduling

Auteur(s) :

Gobert, Maxime [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Université de Mons / University of Mons [UMONS]
Gmys, Jan [Auteur]
Toubeau, Jean-François [Auteur]
Melab, Nouredine [Auteur]
Tuyttens, Daniel [Auteur]
Vallée, François [Auteur]

Titre de la revue :

Algorithms

Pagination :

446

Éditeur :

MDPI

Date de publication :

2022-12

ISSN :

1999-4893

Discipline(s) HAL :

Computer Science [cs]/Operations Research [math.OC]
Statistiques [stat]/Machine Learning [stat.ML]
Informatique [cs]/Modélisation et simulation

Résumé en anglais : [en]

Bayesian Optimization (BO) with Gaussian process regression is a popular framework for the optimization of time-consuming cost functions. However, the joint exploitation of BO and parallel processing capabilities remains ...
Lire la suite >Bayesian Optimization (BO) with Gaussian process regression is a popular framework for the optimization of time-consuming cost functions. However, the joint exploitation of BO and parallel processing capabilities remains challenging, despite intense research efforts over the last decade. In particular, the choice of a suitable batch-acquisition process, responsible for selecting promising candidate solutions for batch-parallel evaluation, is crucial. Even though some general recommendations can be found in the literature, many of its hyperparameters remain problem-specific. Moreover, the limitations of existing approaches in terms of scalability, especially for moderately expensive objective functions, are barely discussed. This work investigates five parallel BO algorithms based on different batch-acquisition processes, applied to the optimal scheduling of Underground Pumped Hydro-Energy Storage stations and classical benchmark functions. Efficient management of such energy-storage units requires parallel BO algorithms able to find solutions in a very restricted time to comply with the responsive energy markets. Our experimental results show that for the considered methods, a batch of four candidates is a good trade-off between execution speed and relevance of the candidates. Analysis of each method’s strengths and weaknesses indicates possible future research directions.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

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

Source :

Harvested from HAL