Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
381609 | Engineering Applications of Artificial Intelligence | 2010 | 10 Pages |
Abstract
In this article a novel algorithm based on the chemotaxis process of Echerichia coli is developed to solve multiobjective optimization problems. The algorithm uses fast nondominated sorting procedure, communication between the colony members and a simple chemotactical strategy to change the bacterial positions in order to explore the search space to find several optimal solutions. The proposed algorithm is validated using 11 benchmark problems and implementing three different performance measures to compare its performance with the NSGA-II genetic algorithm and with the particle swarm-based algorithm NSPSO.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
María Alejandra Guzmán, Alberto Delgado, Jonas De Carvalho,