Aim and scope of the special sessionIn their original versions, nature-inspired algorithms for optimization such as evolutionary algorithms (EAs) and swarm intelligence algorithms (SIAs) 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. The session seeks to promote the discussion and presentation of novel works related with (but not limited to) the following 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
- Surrogate-assisted constrained optimization
- Design of difficult and scalable test functions
Organizers:Helio J.C. Barbosa
Laboratório Nacional de Computação Científica (LNCC), BRAZIL
Universidade Federal de Juiz de Fora, BRAZIL
He is a civil engineer originally interested in finite element methods who turned his attention in the mid-nineties to the design, analysis, and application of nature-inspired metaheuristics to identification, design, and optimization problems in engineering and biology. Since then he has participated in as well as published and reviewed papers for the main conferences in the area. He is a member of ACM SIGEVO, IEEE, and the Computational Intelligence Society (IEEE-CIS). He is also co-chair of the IEEE-CIS Task Force on Nature-Inspired Constrained Optimization.
School of Information Science and Engineering, Central South University, CHINA
He is currently an Associate Professor with the School of Information Science and Engineering, Central South University. His current research interests include evolutionary computation, single-objective optimization, constrained optimization, multiobjective optimization, and their real-world applications. He is a member of the IEEE CIS Task Force on Nature-Inspired Constrained Optimization and the IEEE CIS Task Force on Differential Evolution. He was a reviewer of 40+ international journals and a PC member of 20+ international conferences. He was awarded the Hong Kong Scholar by the Mainland – Hong Kong Joint Postdoctoral Fellows Program, China, in 2013, the Excellent Doctoral Dissertation by Hunan Province, China, in 2013, the New Century Excellent Talents in University by the Ministry of Education, China, in 2013, and the 2015 IEEE Computational Intelligence Society Outstanding PhD Dissertation.
Department of Artificial Intelligence, University of Veracruz, MEXICO
His research interests are the design, analysis and application of nature-inspired algorithms to solve complex optimization problems. He has published over 90 papers in peer-reviewed journals and conferences. He also has one edited book published by Springer and six book chapters published by international publishing companies. He is an IEEE member and also member of the Computational Intelligence Society (IEEE-CIS) and member of the Evolutionary Computation Technical Committee of this Society. He is also co-chair of the IEEE-CIS Task Force on Nature-Inspired Constrained Optimization and member of the IEEE-CIS Task Force on Differential Evolution. Dr. Mezura-Montes is also member of the Systems, Man and Cybernetics Society (IEEE-SMCS) and member of its Soft Computing Technical Committee. Since 2006, Dr. Mezura-Montes has either chaired or co-chaired special sessions in CEC conferences related with constrained optimization.
Important dates:Paper Submissions: 19 December, 2014
Decision notification: 20 February, 2015
Camera ready paper submission: 13 March, 2015