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CoDE-IRIDIA-Metaheuristiques [CoDE-IRIDIA-Metaheuristics] (IRIDIA-Meta)
Faculté des Sciences appliquées - école polytechnique / Brussels School of Engineering (Faculty of Applied Sciences) - Technologies de l'information (unité ULB674)

L'unité CoDE-IRIDIA-Métaheuristiques fait partie du laboratoire IRIDIA (Institut de Recherches Interdisciplinaires et de Développements en Intelligence Artificielle) et du département CoDE (Computer and Decision Engineering) de l'ULB. Les efforts de recherche de l'unité CoDE-IRIDIA-Métaheuristiques se concentrent sur les métaheuristiques, qui sont les techniques les plus puissantes pour la résolution approximative de problèmes computationnels difficiles dans nombre de domaines de l'informatique, de la recherche opérationnelle et de l'ingénierie. L'unité CoDE-IRIDIA-Métaheuristiques est leader parmi les groupes de recherches mondiaux sur des métaheuristiques spécifiques telles que l'optimisation par colonie de fourmis, la recherche locale itérée ainsi que leurs applications à des problèmes NP difficiles et d'optimisation continue. En plus de son expertise sur de nombreux problèmes difficiles d'optimisation, le groupe s'intéresse tout particulièrement à des problèmes dynamiques, multi-objectifs et stochastiques. Un élément fondamental dans le travail de recherche du groupe est l'application d'une solide méthodologie expérimentale et le développement d'outils pour l'étude empirique et la configuration des métaheuristiques. [The CoDE-IRIDIA-Metaheuristiques unit is part of the IRIDIA (Institut de Recherches Interdisciplinaires et de Développements en Intelligence Artificielle) laboratory and of the CoDE (Computer and Decision Engineering) department of ULB. The research focus of the CoDE-IRIDIA-Metaheuristiques research unit is on metaheuristics, which are among the most powerful techniques for the approximate solution of computationally hard problems in many areas of computer science, operations research and engineering. The CoDE-IRIDIA-Metaheuristiques unit is among the world-leading research groups in specific metaheuristics such as ant colony optimization and iterated local search and on their application to NP-hard and to continuous optimization problems. In addition to the expertise on many hard optimization problems, the groups is particularly interested in problems that are dynamic, multi-objective and stochastic. A central point in the research group's research is the application of a sound experimental methodology and the development of tools for the automatic configuration of metaheuristics and other algorithms.]



coordonnées / contact details


CoDE-IRIDIA-Metaheuristiques [CoDE-IRIDIA-Metaheuristics]
tel +32-2-650.27.29 / 31.69, fax +32-2-650.27.15, mdorigo@ulb.ac.be
http://code.ulb.ac.be/iridia.home.php
Campus du Solbosch, Campus du Solbosch, Solbosch, Bât. C, 5ème étage, porte C5.110
CP194/6, avenue F.D. Roosevelt 50, 1050 Bruxelles

Pour en savoir plus, consultez le site web de l'unité.



responsable / head


Prof. Marco DORIGO


composition / members


Leonardo BEZERRA Mohamed Saifullah BIN HUSSIN Mauro BIRATTARI Sabrina DE OLIVEIRA Jérémie DUBOIS-LACOSTE Mascia FRANCO Tianjun LIAO Manuel LOPEZ-IBANEZ Leslie PEREZ Thomas STUTZLE Zhi YUAN


projets / projects


Métaheuristiques [Metaheuristics]
Etude d'approches métaheuristiques pour la résolution de problèmes d'optimisation discrète. La recherche porte autant sur l'étude exhaustive des techniques classiques (comme les algorithmes génétiques, le recuit simulé, la recherche tabou, l'optimisation par colonie de fourmis, la recherche locale itérée) que sur le développement de nouvelles métaheuristiques. [Study of metaheuristic approaches to the solution of discrete optimization problems. The research covers both the study of all the major techniques (like genetic algorithms, simulated annealing, tabu search, and colony optimization, iterated local search) and the development of new metaheuristics.]

Algorithmes basés sur le comportement collectif des fourmis et l'intelligence en essaim. [Ant algorithms and swarm intelligence]
Conception d'algorithmes d'optimisation et de contrôle distribué inspirés par les études du comportement collectif des insectes sociaux. Cette recherche est consacrée à l'étude et à l'utilisation de modèles comportementaux des insectes sociaux en vue d'élaborer des algorithmes distribués. Les applications s'étendent du domaine de la robotique distribuée au dessin graphique et à l'optimisation combinatoire. [Study and design of novel distributed algorithms for optimization and control inspired by the observation of the collective behavior of social insects. This research is devoted to the study and use of models of the behavior of social insects to design distributed algorithms. Applications range from distributed robotics to graph drawing and combinatorial optimization.]



publications





theses


Liao, T. ''Population-based Heuristic Algorithms for Continuous and Mixed Discrete-Continuous Optimization Problems.'' Dir. Prof. M. Dorigo, Co-Dir. Dr. T. Stützle, IRIDIA, ULB, 2013

Montes de Oca, M. ''Incremental Social Learning in Swarm Intelligence Systems.'' Dir. Prof. M. Dorigo, Co-Dir. Dr. T. Stützle, IRIDIA, ULB, 2011

Socha, K. ''Ant Colony Optimization for Continuous and Mixed-Variable Domains.'' Dir. Prof. M. Dorigo, IRIDIA, ULB, 2008

Bianchi, L. ''Ant Colony Optimization and Local Search for the Probabilistic Traveling Salesman Problem: A case Study in Stochastic Combinatorial Optimization.'' Dir. Prof. M. Dorigo, IRIDIA, ULB, 2006

Birattari, M. ''The Problem of Tuning Metaheuristics, as Seen from a Machine Learning Perspective.'' Dir. Prof. M. Dorigo, IRIDIA, ULB, 2004

Blum, C. ''Theoretical and Practical Aspects of Ant Colony Optimization.'' Dir. Prof. M. Dorigo, IRIDIA, ULB, 2004

Di Caro, G. ''Ant Colony Optimization and its Application to Adaptive Routing in Telecommunication Networks.'' Dir. Prof. M. Dorigo, IRIDIA, ULB, 2004

Stützle, T. ''Local Search Algorithms for Combinatorial Problems - Analysis, Algorithms, and New Applications.'' Dir. Prof. W. Bibel, Doctorate in Computer Science, Technische Universität Darmstadt, Germany, 1998

Dorigo, M. ''Ottimizzazione, apprendimento automatico, ed algoritmi basati su metafora naturale (Optimization, Learning, and Natural Algorithms)'' Doctorate in Systems and Information Electronic Engineering, Politecnico di Milano, Italy, 1992

Balaprakash, P. ''Estimation-based Metaheuristics for Stochastic Combinatorial Optimization: Case Studies in Stochastic Routing Problems.'' Dir. Prof. M. Dorigo, Co-Dir. Dr. M. Birattari, Dr. T. Stützle, IRIDIA, ULB - Doctorat



collaborations


Prof. Ruben Ruiz, Universidad Politécnica de Valencia, Valencia, Espagne

Prof. Holger Hoos, University of British Columbia, Department of Computer Science, Vancouver, Canada

Prof. Luca Maria Gambardella, University of Applied Science of Southern Switzerland, IDSIA, Lugano, Suisse

Prof. Ben Paechter, Napier University, Edinburgh, Grande-Bretagne

Prof. Yves Deville, Université catholique de Louvain, Louvain-la-Neuve, Belgique

Prof. Andrea Roli, Università di Bologna, DEIS - Dept. of electronics, computer science and systems, Cesena, Italie

Prof. António Gaspar Lopes da Cunha, University of Minho, Dep. of Polymer Engineering, Portugal



prix / awards


Premio Italiano per l'Intelligenza Artifciale 1996. - Marco DORIGO

Fellow of the IEEE (Institute of Electronical Engineers), 2006. - Marco DORIGO

Fellow of ECCAI (European Coordinating Committee for Artificial Intelligence), 2007. - Marco DORIGO

Dr. Dorigo's Marie Curie fellowship results have been selected by the European Commission as one of the 'MARIE CURIE FELLOWSHIPS SUCCESS STORIES' (document EUR 17763 published by the European Commision in December 1997) - Marco DORIGO

''FNRS - Dr A. De Leeuw-Damry-Bourlart award in Applied Sciences'' for his fundamental contributions to the foundation of the swarm intelligence research field, 2005. - Marco DORIGO

Marie Curie Excellence Award for research on Ant Colony Optimization and Ant Algorithms, 2003. - Marco DORIGO

CajAstur International Prize for Soft Computing, Spain, 2007 - Marco DORIGO

The paper ''Adaptive Anytime Two-Phase Local Search'' has received the best paper award of the LION 4 conference, Venice, Italy, 2010 - Thomas STUTZLE

The paper ''PLANTS: Application of Ant Colony Optimization to Structure-Based Drug Design'' co-authored by Oliver Korb, Thomas Stützle and Thomas Exner, has received the best paper award of the ANTS'2006 conference. - Thomas STUTZLE

The paper ''An Experimental Investigation of Iterated Local Search for Coloring Graphs'', co-authored by Luis Paquete and Thomas Stützle, has received the best paper award of the EvoCOP'02 workshop. - Thomas STUTZLE

Marco Dorigo was awarded an ERC Advanced Grant for the project ''E-Swarm: Engineering Swarm Intelligence Systems'' - Marco DORIGO

The paper ''The impact of design choices of multi-objective ant colony optimization algorithms on performance: An experimental study on the biobjective TSP'' has received the best paper award of the ACO-SI track at GECCO 2010. - Manuel LOPEZ-IBANEZ Thomas STUTZLE

The paper ''An Incremental Ant Colony Algorithm with Local Search for Continuous Optimization'' has received the best paper award of the ACO-SI track at GECCO 2011. - Marco DORIGO Tianjun LIAO Marco MONTES DE OCA Thomas STUTZLE

The paper ''A racing algorithm for configuring metaheuristics'' GECCO 2012 Impact Award, which was given for the most cited paper of the GECCO 2002 conference. - Mauro BIRATTARI Thomas STUTZLE



savoir-faire/équipements / know-how, equipment


Rack de plus de 1000 cores



mots clés pour non-spécialistes / keywords for non-specialists


configuration automatique des algorithmes metaheuristiques optimisation recherche locale recherche locale stochastique


disciplines et mots clés / disciplines and keywords


Cybernétique Intelligence artificielle Recherche opérationnelle Théorie des algorithmes

algorithmes des fourmis algorithmes génétiques distributed optimization heuristiques intelligence en essaim métaheuristiques optimisation par colonies de fourmis recherche locale itérée recherche tabou recuit simulé


codes technologiques DGTRE


Informatique, théorie des systèmes Intelligence artificielle