Hybrid Metaheuristics

Third International Workshop, HM 2006 Gran Canaria, Spain, October 13-14, 2006 Proceedings

  • Francisco Almeida
  • María J. Blesa Aguilera
  • Christian Blum
  • José Marcos Moreno Vega
  • Melquíades Pérez Pérez
  • Andrea Roli
  • Michael Sampels
Conference proceedings HM 2006

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4030)

Table of contents

  1. Front Matter
  2. Günther R. Raidl
    Pages 1-12
  3. Toshihide Ibaraki, Kouji Nakamura
    Pages 13-27
  4. Luis delaOssa, José A. Gámez, José M. Puerta
    Pages 42-56
  5. Laetitia Jourdan, Clarisse Dhaenens, El-Ghazali Talbi
    Pages 57-69
  6. Inmaculada Rodríguez-Martín, Juan-José Salazar-González
    Pages 70-81
  7. Christian Blum, Mateu Yábar Vallès
    Pages 94-109
  8. Panagiotis P. Repoussis, Dimitris C. Paraskevopoulos, Christos D. Tarantilis, George Ioannou
    Pages 124-138
  9. Madalina Ionita, Cornelius Croitoru, Mihaela Breaban
    Pages 139-149
  10. Carlos Cotta, Iván Dotú, Antonio J. Fernández, Pascal Van Hentenryck
    Pages 150-161
  11. Marco Chiarandini, Thomas Stützle, Kim S. Larsen
    Pages 162-177
  12. Thomas Bartz-Beielstein, Mike Preuss, Günter Rudolph
    Pages 178-191
  13. Back Matter

About these proceedings


The International Workshop on Hybrid Metaheuristics reached its third edition with HM 2006. The active and successful participation in the past editions was a clear indication that the research community on metaheuristics and related areas felt the need for a forum to discuss speci?c aspects of hybridization of metaheuristics. The selection of papers for HM 2006 consolidated some of the mainstream issues that have emerged from the past editions. Firstly, there are prominent examples of e?ective hybrid techniques whose design and implementation were motivated by challenging real-world applications. We believe this is particularly important for two reasons: on the one hand, researchers are conscious that the primary goal of developing algorithms is to solve relevant real-life problems; on the other hand, the path towarde?cient solving methods for practical problems is a source of new outstanding ideas and theories. A second important issue is that the research community on metaheur- tics has become increasingly interested in and open to techniques and methods known from arti?cial intelligence (AI) and operations research (OR). So far, the most representative examples of such integration have been the use of AI/OR techniques as subordinates of metaheuristic methods. As a historical and - ymological note, this is in perfect accordance with the original meaning of a metaheuristic as a “general strategy controlling a subordinate heuristic. ” The awareness of the need for a sound experimental methodology is a third keypoint.


Performance algorithmics algorithms approximation algorithms data analysis data mining evolutionary algorithm evolutionary algorithms expert system genetic algorithms heuristics hybridization multi-objective optimizatio optimization programming

Editors and affiliations

  • Francisco Almeida
    • 1
  • María J. Blesa Aguilera
    • 2
  • Christian Blum
    • 3
  • José Marcos Moreno Vega
    • 4
  • Melquíades Pérez Pérez
    • 5
  • Andrea Roli
    • 6
  • Michael Sampels
    • 7
  1. 1.Department of Statistics and Computer ScienceLa Laguna University Spain 
  2. 2.Universitat Politècnica de CatalunyaBarcelonaSpain
  3. 3.ALBCOM, Dept. Llenguatges i Sistemes InformàticsUniversitat Politècnica de CatalunyaBarcelonaSpain
  4. 4.DEIOCUniversidad de La Laguna, Escuela Técnica Superior en Ingeniería InformáticaLa Laguna, TenerifeSpain
  5. 5.Escuela Técnica Superior en Ingeniería InformáticaUniversidad de La LagunaLa Laguna, TenerifeSpain
  6. 6.DEIS, Campus of Cesena Alma Mater StudiorumUniversità di BolognaCesenaItaly
  7. 7.Université Libre de BruxellesBruxellesBelgium

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science Computer Science (R0)
  • Print ISBN 978-3-540-46384-9
  • Online ISBN 978-3-540-46385-6
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site