Bio-inspired metaheuristics

Members Collaborations

Group Leader

Dr. Carlos A. Coello Coello (México)

Executive Summary

Metaheuristics are an important alternative to solve complex search and optimization problems that are not tractable by deterministic methods. During the end of the Twentieth Century and the beginning of this one, metaheuristics raised to become a widely used paradigm within optimization and classification.
The Computer Science group at the LAFMIA located at CINVESTAV-IPN works mainly on single- and multi-objective optimization using bio-inspired metaheuristics, such as evolutionary algorithms, particle swarm optimization, and ant colony optimization.