Performance Analysis-based GA Parameter Selection and Increase of μ GA Accuracy by Gradual Contraction of Solution Space (CROSBI ID 546595)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Dužanec, Darko ; Kovačić, Zdenko
engleski
Performance Analysis-based GA Parameter Selection and Increase of μ GA Accuracy by Gradual Contraction of Solution Space
Although methods for design of genetic algorithms (GA) are well established, general expressions for determination of optimal GA parameters are still missing. There is also a problem of possible inaccuracy of a found solution. This paper describes a GA performance analysis for a selected vector-based optimization problem that has led to useful GA parameter selection criteria. The paper also describes a new method for increasing the precision of a complementary micro genetic algorithm (μ GA) by enforcing gradual contraction of the space of candidate solutions during optimization. The enhanced μ GA has been tested on the model of a 13-DOF tentacle robot, and the performance analysis showed significant improvement of accuracy without affecting the duration of the algorithm.
Microgenetic algorithms; inverse kinematics; robot control
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Podaci o prilogu
2009.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 2009 IEEE International Conference on Industrial Technology (ICIT)
Melbourne:
Podaci o skupu
The 2009 IEEE International Conference on Industrial Technology (ICIT)
predavanje
10.02.2009-13.02.2009
Gippsland, Australija