Titre :

Automatic Design of Hybrid Stochastic Local Search Metaheuristics

Auteur(s) :

Kessaci, Marie-Eleonore [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Mascia, Franco [Auteur]
Fonds de la Recherche Scientifique [FNRS]
Institut de Recherches interdisciplinaires et de Développements en Intelligence Artificielle [Bruxelles] [IRIDIA]
López-Ibáñez, Manuel [Auteur]
Fonds de la Recherche Scientifique [FNRS]
Institut de Recherches interdisciplinaires et de Développements en Intelligence Artificielle [Bruxelles] [IRIDIA]
Stützle., Thomas [Auteur]
Fonds de la Recherche Scientifique [FNRS]
Institut de Recherches interdisciplinaires et de Développements en Intelligence Artificielle [Bruxelles] [IRIDIA]

Éditeur(s) ou directeur(s) scientifique(s) :

María J. Blesa
Christian Blum
Paola Festa
Andrea Roli
and Michael Sampels

Titre de la manifestation scientifique :

HM 2013 - 8th International Workshop on Hybrid Metaheuristics

Ville :

Ischia

Pays :

Italie

Date de début de la manifestation scientifique :

2013-05-23

Titre de l’ouvrage :

LNCS

Titre de la revue :

HM 2013: Hybrid Metaheuristics

Éditeur :

Springer

Date de publication :

2013

Discipline(s) HAL :

Informatique [cs]/Mathématique discrète [cs.DM]
Computer Science [cs]/Operations Research [math.OC]

Résumé en anglais : [en]

Many stochastic local search (SLS) methods rely on the manipulation of single solutions at each of the search steps. Examples are iterative improvement, iterated local search, simulated annealing, variable neighborhood ...
Lire la suite >Many stochastic local search (SLS) methods rely on the manipulation of single solutions at each of the search steps. Examples are iterative improvement, iterated local search, simulated annealing, variable neighborhood search, and iterated greedy. These SLS methods are the basis of many state-of-the-art algorithms for hard combinatorial optimization problems. Often, several of these SLS methods are combined with each other to improve performance. We propose here a practical, unified structure that encompasses several such SLS methods. The proposed structure is unified because it integrates these metaheuristics into a single structure from which we can not only instantiate each of them, but we also can generate complex combinations and variants. Moreover, the structure is practical since we propose a method to instantiate actual algorithms for practical problems in a semi-automatic fashion. The method presented in this work implements a general local search structure as a grammar; an instantiation of such a grammar is a program that can be compiled into executable form. We propose to find the appropriate grammar instantiation for a particular problem by means of automatic configuration. The result is a semi-automatic system that, with little human effort, is able to generate powerful hybrid SLS algorithms.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