Metaheuristics, such as simulated annealing, genetic and evolutionary algorithms, tabu search, ant colony optimization, scatter search and iterated local search, have received considerable interest in the fields of applied artificial intelligence and combinatorial optimization. Plenty of hard problems in a huge variety of areas, including bioinformatics, logistics, engineering, business, etc., have been tackled successfully with metaheuristic approaches. For many problems the resulting algorithms are considered to be the state-of-the-art methods.
For many years the main focus of research was on the application of single metaheuristics to given problems. In recent years, it has become evident that the concentration on a sole metaheuristic is rather restrictive. A skilled combination of concepts of different metaheuristics, a so called hybrid metaheuristic, can provide a more efficient behavior and a higher flexibility when dealing with real-world and large-scale problems.
A quite new field of research is also the hybridization of metaheuristics with other techniques. Recently, it was observed that the incorporation of more classical artificial intelligence and operations research techniques in metaheuristics can be very beneficial. An example is the use of constraint programming techniques, such as domain filtering and variable fixing, in order to shrink the search space that has to be searched by a metaheuristic. Another example is the incorporation of tree search procedures in metaheuristics.
The design and implementation of hybrid metaheuristics rises problems going beyond questions about the design of a single metaheuristic. Choice and tuning of parameters is for example enlarged by the problem of how to achieve a proper interaction of different algorithm components. Interaction can take place at low-level, using functions from different metaheuristics, but also at high-level, e.g., using a portfolio of metaheuristics for automated hybridization.
It is implicit with the subject of the workshop that contributions should address the combination and comparison of different metaheuristic components and concepts. In contrast to standard research in metaheuristics, also negative results - e.g., a component shows poor performance for the majority of test instances - are of considerable importance in hybridization. Such results have often been ignored, at least in the publication of results in standard metaheuristics research. Further, the above mentioned enlarged selection of parameters will attract more attention to this part of designing algorithms.
In summary, with this workshop we aim at papers that give good examples for carefully designed and well-analyzed hybrid metaheuristics. The extraction of guidelines for the general design of hybrid metaheuristics would be desirable.
Researchers are invited to submit papers of any length but not more than 12 pages to hm2004@iridia.ulb.ac.be. Every paper will be reviewed by at least two members of the programme committee. Researchers are explicitly encouraged to address statistical validity of their results, if they compare different approaches. Source code and problem instances should (if relevant) be made available on the Internet. It is recommended to use the standard LaTeX article style when preparing the submission.
| Submission of papers: | April 24, 2004 |
| Notification of acceptance: | May 23, 2004 |
| Camera-ready papers: | June 4, 2004 |
The accepted papers will be included in the workshop proceedings. Authors of selected workshop papers will be invited to submit an extended version of their papers for consideration in a special issue of the Journal of Mathematical Modelling and Algorithms with Kluwer Academic Publishers that the organizers are going to edit.
All workshop participants are expected to register for the main ECAI 2004, conference.
003
Sameh Al-Shihabi:
Ants for Sampling in the Nested Partition Algorithm
004
Noureddine Bouhmala:
Combining Local Search with the Multilevel Paradigm for the Traveling
Salesman Problem
006
Miguel García-Torres, Félix García-López,
Belén Melián-Batista, José A. Moreno-Pérez,
J. Marcos Moreno-Vega:
Solving Feature Subset Selection Problem by a Hybrid Metaheuristic
008
Jesús David Beltrán, Jose Eduardo Calderón, Rayco
Jorge Cabrera, José A. Moreno Pérez, J. Marcos Moreno-Vega:
GRASP-VNS hybrid for the Strip Packing Problem
009
Kaveh Sheibani:
An Adaptive Greedy Genetic Algorithm Using Fuzzy Reasoning for the
Travelling Salesman Problem
010
P. Chardaire, G. P. McKeown, J. A. Maki:
Hybridizing GRASP, PROBE and Path Relinking
011
Marcos Henrique Ribeiro, Viviane Trindade, Alexandre Plastino, Simone
Martins:
Hybridization of GRASP Metaheuristics with Data Mining Techniques
012
Shunji Umetani, Mutsunori Yagiura, Toshihide Ibaraki:
One-dimensional cutting stock problem with a given number of setups:
a hybrid approach of metaheuristics and linear programming
014
Dagmar Monett-Díaz:
+CARPS: Configuration of Metaheuristics based on JADE Agents
015
A. Gaspar-Cunha, Armando S. Vieira:
A Hybrid Multi-Objective Evolutionary Algorithm Using an Inverse Neural
Network
016
Marc Reimann, Marco Laumanns:
A hybrid ACO algorithm for the Capacitated Minimum Spanning Tree Problem
017
El-Ghazali Talbi, Vincent Bachelet:
COSEARCH: A Parallel Co-evolutionary Metaheuristic
021
Roberto R. Souto, Haroldo F. de Campos Velho, Stephan Stephany, Sandra
A. Sandri:
Reconstruction of Chlorophyll Concentration Profile in Offshore Ocean
Water using a Parallel Ant Colony Code
Christian Blum,
Université Libre de Bruxelles, Belgium
Andrea Roli,
Università "G. D'Annunzio", Chieti, Italy
Michael Sampels,
Université Libre de Bruxelles, Belgium
Maria Blesa, Universitat Politècnica de Catalunya, Spain
Marco Dorigo, Université Libre de Bruxelles, Belgium
Filippo Focacci, ILOG, France
Joshua Knowles, University of Manchester, England
Andrea Lodi, Università di Bologna, Italy
Monaldo Mastrolilli, IDSIA, Switzerland
Daniel Merkle, Universität Leipzig, Germany
Michela Milano, Università di Bologna, Italy
Olivia Rossi-Doria, Napier University, Edinburgh, Scotland
Thomas Stützle, Technische Universität Darmstadt, Germany
Christian Blum, Michael Sampels
Université Libre de Bruxelles
Institut de Recherches Interdisciplinaires
et de Développements en Intelligence Artificielle
CP 194/6
Av. Franklin D. Roosevelt 50
1050 Bruxelles
BELGIUM
Tel +32-2-650-3168
Fax +32-2-650-2715
hm2004@iridia.ulb.ac.be