The Fourth International Workshop on Frontiers in Evolutionary Algorithms (FEA 2002)

                  Research Triangle Park, North Carolina, USA
                               March 8-13, 2002

                            In conjunction with

            Sixth Joint Conference on Information Sciences

Mission Publication policy Scope Committees Paper Submission   Dates Invited speech

Mission Statement

The FEA workshop is intended as a  forum for the presentation of new results as well as review works on the field of Evolutionary Algorithms. The term  "Evolutionary Algorithms" encompasses terms like Genetic Algorithms, Genetic Programming, Evolution Strategies, Evolutionary Computation, Evolvable Hardware and others that denote computational strategies inspired in natural evolution  and genetic coding.

These algorithms and methods have become a tool of common use by the engineers and  scientists that face complex and ill posed optimization problems, either stationary or dynamic in nature. As a natural consequence the range of applications is steadily growing. The workshop mission is the presentation and publication of quality research work on fundamental issues and application of Evolutionary Algorithms.

The collaboration of the program committee members has been key to ensure the quality of the contributions in past instances of the workshop. Selected papers have been published in a special issue of the Information Sciences International Journal.

Publication Policy

The proposed publication policy will be as follows:

We invite the submission of

Scope of the Workshop

Topics of interest include, but are not limited to:

1 Fundamental Issues

Convergence results
Classifier systems
Representation and coding issues
Co-evolutionary Algorithms
Evolution Algorithms in Multi-Agent Computing
Complexity Reduction
2 Applications
Signal Processing
Image Processing
Computer Vision
Multimedia applications
Financial applications and Time Series prediction
Data Mining & Warehousing
Information Retrieval
Classification and Clustering
Regression and Model Identification
Machine Learning
Pattern Recognition
Knowledge Discovery
Constraint Satisfaction and Constrained Optimization
Adaptive and Anticipative Control
Static and Dynamic Optimization
Evolutive robotics
Evolutive Knowbots
Autonomous Systems



General Chairs

Manuel Grana Romay, Universidad Pais Vasco, Spain
Richard Duro (Univ. La Coruna, Spain)

Program Committee

Jarmo Alander (Univ. Vaasa, Finland)
Enrique Alba (Univ. Malaga, Spain)
Thomas Baeck (Dortmund, Germany)
Helio J.C.Barbosa (LNCC/CNPq .Brasil)
Hilan Bensusan (University Bristol, UK)
Peter Bentley (UK)
Maumita Bhattacharya(Monash University, Australia)
Stefano Cagnoni (Univ. Parma, Italy)
Erick Cantu-Paz (Lawrence Livermore Nat. Lab., USA)
Yuehui Chen (Memory-Tech Corporation, Japan)
Carlos A. Coello Coello (Mexico)
Marie Cottrell (Univ. Paris 1, France)
Kelly Crawford (USA)
Alicia d'Anjou (Univ. Pais Vasco, Spain)
Dipankar Dasgupta (Memphis, USA)
Kalyanmoy Deb (Indian Institute of Technology Kanpur, India)
Marco Dorigo (Universite Libre de Bruxelles, Belgium)
Gerry V. Dozier  (Auburn Univ. USA)
Richard Duro (Univ. La Coruna, Spain)
Candida Ferreira (GepSoft, Portugal)
Alex Freitas (PUC-PR, Brazil)
Max Garzon (Memphis University, USA)
Andreas Geyer-Schulz(Universität Karlsruhe , De)
Christophe Giraud-Carrier (ELCA Informatique SA, Switzerland)
Robert Ghanea-Hercock (BT, UK)
David Goldberg (U. Illinois,USA)
Manuel Grana (Univ. Pais Vasco, Spain)
Darko Grundler (Croatia)
Francisco Herrera (Univ. Granada, Spain)
Vasant Honavar (Iowa State University ,USA)
Frank Hoffmann(Royal Institute of Technology, Sweden)
Spyros A.  Kazarlis (Univ. Thessaloniki, Greece)
Tatiana Kalganova (Brunel University, UK)
Sami Khuri (San Jose State University, USA)
Hod Lipson (Cornell University, USA)
Evelyne Lutton (INRIA, France)
John  A. W. McCall (Robert Gordon Univ., UK)
J.J. Merelo (Universidad de Granada, Spain)
Jae C.Oh (Syracuse Univ., USA)
Bjorn Olsson (University of Skovde, Sweden)
Ian C. Parmee (University of Plymouth, U.K.)
Frank Paseman, (University of Jena, De)
Andres Perez-Uribe (Swiss Federal Institute of Technology-Lausanne)
Jennifer L.Pittman (Penn State Univ. USA)
Alberto Prieto (Univ. Granada, Spain)
Robert G. Reynolds (Wayne Univ., USA)
Leon Rothkrantz (University of Delft, Netherlands)
Marco Ruso (Universita degli Studi Mesina, Italy)
Francisco Sandoval (Universidad de Malaga, Spain)
Jose Santos (Univ. Da Coruña, Spain)
Marc Schoenauer (CMA - Ecole Polytechnique, Palaiseau, France)
Shigeyoshi Tsutsui (Hannan University, Japan)
J. Luis Verdegay (Univ. Granada, Spain)
Thomas Villmann (University Leipzig, Germany)
Klaus Weinert (University Dortmund, Germany)
Man Leung Wong (Lingnan University, Hong Kong)
Xin Yao (University of Birmingham, U.K.)
Yun Seog Yeun (Daejin Jin U. Korea)

Publicity and local organization commitee

Jose Antonio Becerra Permuy
Francisco Bellas Bouza
Adolfo Lamas Rodriguez
Juan Luis Crespo Mariño
Ramon Luaces Cuetara
Lorena Carballo
M. Carmen Hernandez

Invited speech

The JCIS conference organization has invited Dr Thomas Baeck, to give a Semi-Plenary speech

Adaptive Business Intelligence based on Evolution Strategies:

Application Examples and some Links to Theory.

Self-adaptive software is one of the key  discoveries in the  field of  evolutionary computation, originally invented in the framework  of the German evolution strategies. Self-adaptivity enables the algorithm  to dynamically adapt to the problem characteristics and even to cope with changing environmental  conditions - as  they  occur in  unforeseeable ways in any kind of business application.

In evolution strategies, self-adaptability is generated by means of an evolutionary search process that  operates on  the solutions generated  by the method as well as on the evolution strategy's parameters, i.e., the algorithm itself. By focusing on  some basic  algorithmic variants  of  evolution strategies,  the fundamental idea  of self-adaptation is  outlined in this talk.

Applications of evolution strategies  include the whole range of business activities, including R & D, technical design, control,   production,  quality   control,  logistics,  and management  decision support. While such  examples can of course not be disclosed, we illustrate  the capabilities of evolution strategies by giving some  simpler  application examples to problems occurring in traffic control  and engineering.

Some theoretical  results about  evolution strategies  will be used to  clarify the  complexity of questions  still  to be addressed  in  this  field.

Paper submission procedures

Submission instructions may change.

Basic submission procedure: send by electronic mail the postscript of pdf version of the abstract (4 pages maximum) to


Hard copies are not encouraged. If it is impossible to perform the electronic submission, then send 4 hard copies of the abstract to the following address:

Dr. Manuel Graña,
Departamento Ciencias de la Computacion, UPV/EHU
Facultad de Informatica,
Paseo Manuel de Lardizabal,
20009 San Sebastian, Spain.

Candidate long papers for the AIP volume can be sent along with the abstract.

As the reviewing process will be performed through electronic means the PostScript or PDF version  of the paper is preferred.


Short paper submission deadline: October 1, 2001
Notification of acceptance:  November 15, 2001
Camera ready paper due: December 15, 2001
Workshop date:  March 8, 2002