NSGA WITH ELITISM APPLIED TO SOLVE MULTIOBJECTIVE OPTIMIZATION PROBLEMS

Authors

  • J. A. Vasconcelos
  • R. L. S. Adriano
  • D. A. G. Vieira
  • G. F. D. Souza
  • H. S. Azevedo

Keywords:

jmoe

Abstract

In this paper the effects of elitism in the Nondominated Sorting Genetic Algorithm (NSGA) are analyzed. Three different kinds of elitism: standard, clustering and Parks & Miller techniques are investigated using two test problems. For the studied problems, the Parks & Miller mechanism generated the best results. Finally, the NSGA with Parks & Miller elitism was applied to determine the nondominated front for a storage magnetic energy system and the IEEE 30- node system. Simulation results obtained suggest the effectiveness of this proposed approach to solve real world problems.

References

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Published

2002-05-05

How to Cite

J. A. Vasconcelos, R. L. S. Adriano, D. A. G. Vieira, G. F. D. Souza, & H. S. Azevedo. (2002). NSGA WITH ELITISM APPLIED TO SOLVE MULTIOBJECTIVE OPTIMIZATION PROBLEMS. Journal of Microwaves, Optoelectronics and Electromagnetic Applications (JMOe), 2(6), 59-69. Retrieved from http://www.jmoe.org/index.php/jmoe/article/view/85

Issue

Section

Regular Papers