National Laboratory for Scientific Computation (LNCC), BRAZIL.
Universidade Federal de Juiz de Fora, BRAZIL.
School of Information Science and Engineering, Central South University, CHINA.
In 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 for single-, multi-, and many-objective optimization, using
different nature-inspired techniques.
The session seeks to promote the discussion and presentation of novel works related with the following (but not limited to) issues:
Please follow the CEC 2017 instructions for authors.