Helio J.C.
Barbosa
National Laboratory for Scientific Computation (LNCC), BRAZIL.
Universidade Federal de Juiz de Fora, BRAZIL.
Yong
Wang
School of Information Science and Engineering, Central South University, CHINA.
AND
Efrén Mezura-Montes
University of Veracruz, MEXICO.
emezura@uv.mx
In
their original versions, nature-inspired algorithms for optimization
such as evolutionary algorithms (EAs) and swarm intelligence (SI) are
designed to sample unconstrained search spaces. Therefore, a
considerable amount of research has been dedicated to adapt them to
deal with constrained search spaces. The objective of the session is to
present the most recent advances in constrained optimization using
different nature-inspired techniques.
Scope
The session seeks to promote the discussion and presentation of novel works related with the following (but not limited to) issues:
- Novel constraint-handling techniques
- Novel/adapted search-engines for constrained optimization
- Memetic algorithms in constrained search spaces.
- Parameter adaptation in constrained optimization
- Mixed (discrete-continuous) constrained optimization.
- Theoretical analysis and complexity of algorithms in constrained
- optimization.
- Performance evaluation of algorithms in constrained optimization.
- Constraint-handling techniques in multi and many-objective optimization
- Dynamic constraint-handling
- Design of difficult and scalable test functions
- Applications.
Program Committee (partial list, more PC members to be added)
- Heder S. Bernardino, BRAZIL
- Eduardo G. Carrano, BRAZIL
- Felipe Campelo, BRAZIL
- Nareli Cruz-Cortés, MEXICO
- Wenyin Gong, CHINA
- Ricardo Landa-Becerra, MEXICO
- Guillermo Leguizamón, ARGENTINA
- Afonso C.C. Lemonge, BRAZIL
- Ricardo C.H. Takahashi, BRAZIL
- Gregorio Toscano-Pulido, MEXICO
- Elizabeth Wanner, BRAZIL
- Xinchao Zhao, CHINA
Please follow the CEC 2015 instructions for authors.
Copyright 2012 Mauricio Damián Araoz. All rights reserved.