• English
    • français
  • Help
  •  | 
  • Contact
  •  | 
  • About
  •  | 
  • Login
  • HAL portal
  •  | 
  • Pages Pro
  • EN
  •  / 
  • FR
View Item 
  •   LillOA Home
  • Liste des unités
  • Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
  • View Item
  •   LillOA Home
  • Liste des unités
  • Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Automatic Design of Hybrid Stochastic Local ...
  • BibTeX
  • CSV
  • Excel
  • RIS

Document type :
Communication dans un congrès avec actes
DOI :
10.1007/978-3-642-38516-2_12
Title :
Automatic Design of Hybrid Stochastic Local Search Metaheuristics
Author(s) :
Kessaci, Marie-Éléonore [Auteur] refId
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]
Scientific editor(s) :
María J. Blesa
Christian Blum
Paola Festa
Andrea Roli
and Michael Sampels
Conference title :
HM 2013 - 8th International Workshop on Hybrid Metaheuristics
City :
Ischia
Country :
Italie
Start date of the conference :
2013-05-23
Book title :
LNCS
Journal title :
HM 2013: Hybrid Metaheuristics
Publisher :
Springer
Publication date :
2013
HAL domain(s) :
Informatique [cs]/Mathématique discrète [cs.DM]
Informatique [cs]/Recherche opérationnelle [cs.RO]
English abstract : [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 ...
Show more >
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.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
Files
Thumbnail
  • https://dipot.ulb.ac.be/dspace/bitstream/2013/154445/1/34.pdf
  • Open access
  • Access the document
Université de Lille

Mentions légales
Université de Lille © 2017