An Experimental Comparison of Multiobjective Algorithms: NSGA-II and OMOPSO

Author

Godinez, Adriana Cortés ; Espinosa, Luis Ernesto Mancilla ; Montes, Efrén Mezura

Author_Institution

Inst. Tecnol. de Leon, Guanajuato, Mexico

fYear

2010

fDate

Sept. 28 2010-Oct. 1 2010

Firstpage

28

Lastpage

33

Abstract

The optimization of multi objective problems is currently an area of important research and development. The importance of type of problems has allowed the development of multiple metaheuristics for their solution. To determine which multi objective metaheuristic has the best performance with respect to a problem, in this article an experimental comparison between two of them: Sorting Genetic Algorithm No dominated-II (NSGA-II) and Multi Objective Particle Swarm Optimization (MOPS) using ZDT test functions is made. The results obtained by both algorithms are compared and analyzed based on different performance metrics that evaluate both the dispersion of the solutions on the Pareto front, and its proximity to it.

Keywords

Pareto optimisation; genetic algorithms; particle swarm optimisation; research and development; MOPS; NSGA-II; Pareto front; ZDT test functions; metaheuristics; multi objective particle swarm optimization; research and development; sorting genetic algorithm no dominated-II; Erbium; Lead; Measurement; Optimization; Particle swarm optimization; Sorting; NSGA-II; OMOPSO; comparative study; multiobjective optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronics, Robotics and Automotive Mechanics Conference (CERMA), 2010

Conference_Location

Morelos

Print_ISBN

978-1-4244-8149-1

Type

conf

DOI

10.1109/CERMA.2010.13

Filename

5692307