MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework

Blot, Aymeric; Hoos, Holger; Jourdan, Laetitia; Kessaci, Marie-Eleonore; Trautmann, Heike

Document type :

Communication dans un congrès avec actes

DOI :

10.1007/978-3-319-50349-3_3

Title :

MO-ParamILS: A Multi-objective Automatic Algorithm Configuration Framework

Author(s) :

Blot, Aymeric [Auteur correspondant]
Université de Lille
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
École normale supérieure - Rennes [ENS Rennes]
University of British Columbia [UBC]
Hoos, Holger [Auteur]
University of British Columbia [UBC]
Jourdan, Laetitia [Auteur]

Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Université de Lille
Kessaci, Marie-Eleonore [Auteur]

Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Université de Lille
Trautmann, Heike [Auteur]
Westfälische Wilhelms-Universität Münster = University of Münster [WWU]

Conference title :

Learning and Intelligent Optimization

City :

Ischia

Country :

Italie

Start date of the conference :

2016-05-29

Book title :

Learning and Intelligent Optimization

Journal title :

Lecture Notes in Computer Science

English keyword(s) :

Local Search Algorithms
Algorithm Configuration
Multi-objective Optimisation
Parameter Tuning

HAL domain(s) :

Computer Science [cs]/Operations Research [math.OC]

English abstract : [en]

Automated algorithm configuration procedures play an increasingly important role in the development and application of algorithms for a wide range of computationally challenging problems. Until very recently, these ...
Show more >Automated algorithm configuration procedures play an increasingly important role in the development and application of algorithms for a wide range of computationally challenging problems. Until very recently, these configuration procedures were limited to optimising a single performance objective, such as the running time or solution quality achieved by the algorithm being configured. However, in many applications there is more than one performance objective of interest. This gives rise to the multi-objective automatic algorithm configuration problem, which involves finding a Pareto set of configurations of a given target algorithm that characterises trade-offs between multiple performance objectives. In this work, we introduce MO-ParamILS, a multi-objective extension of the state-of-the-art single-objective algorithm configuration framework ParamILS, and demonstrate that it produces good results on several challenging bi-objective algorithm configuration scenarios compared to a base-line obtained from using a state-of-the-art single-objective algorithm configurator.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

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