A novel multiobjective optimization algorithm based on bacterial chemotaxis

Authors:
María Alejandra Guzmán;Alberto Delgado;Jonas De Carvalho
Affiliations:
Department of Mechanical and Mechatronics Engineering, National University of Colombia, Carrera 30 # 45-03 - Building 453, Bogota, Colombia and Department of Mechanical Engineering, EESC-Universit ...;Department of Electrical and Electronics Engineering, National University of Colombia, Carrera 30 # 45-03 - Building 453, Bogota, Colombia;Department of Mechanical Engineering, EESC-University of Sao Paulo, Avenida do Trabalhador sãocarlense 400, Sao Carlos, Brazil
Venue:
Engineering Applications of Artificial Intelligence
Year:
2010

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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.