TY - GEN
T1 - Performance optimization of GA based planar mechanism synthesis
AU - Lugo-González, E.
AU - Hernández-Gómez, L. H.
AU - Ponce-Reynoso, R.
AU - Velázquez-Sánchez, A. T.G.
AU - Merchán-Cruz, E. A.
AU - Ramírez-Gordillo, J.
PY - 2010
Y1 - 2010
N2 - This paper present the analysis of the manipulation of some parameters to improve the performance of genetic algorithm based planar mechanism synthesis, such as the mutation and crossover probability and the population size, applied to a specific case of dimensional optimization, to obtain the best results for a group of design variables that achieve the best performance in the design of planar mechanisms, whose evaluation is expressed by means of an objective function that has to meet certain restrictions or requirements to minimize the error between the desired and generated trajectory of the coupler link, since the objective of path generation is to find the mechanism that properly describes the desired curve in shape, size, orientation and position. Two examples are given for illustration, for which the mentioned parameters are manipulated to see the effects of these on the final result for the minimization of the error and the value of variables involved in the dimensions of the links and the motion angles.
AB - This paper present the analysis of the manipulation of some parameters to improve the performance of genetic algorithm based planar mechanism synthesis, such as the mutation and crossover probability and the population size, applied to a specific case of dimensional optimization, to obtain the best results for a group of design variables that achieve the best performance in the design of planar mechanisms, whose evaluation is expressed by means of an objective function that has to meet certain restrictions or requirements to minimize the error between the desired and generated trajectory of the coupler link, since the objective of path generation is to find the mechanism that properly describes the desired curve in shape, size, orientation and position. Two examples are given for illustration, for which the mentioned parameters are manipulated to see the effects of these on the final result for the minimization of the error and the value of variables involved in the dimensions of the links and the motion angles.
KW - Genetic algorithm
KW - Optimization
KW - Performance
KW - Planar mechanisms
UR - http://www.scopus.com/inward/record.url?scp=79951684957&partnerID=8YFLogxK
U2 - 10.1109/CERMA.2010.26
DO - 10.1109/CERMA.2010.26
M3 - Contribución a la conferencia
AN - SCOPUS:79951684957
SN - 9780769542041
T3 - Proceedings - 2010 IEEE Electronics, Robotics and Automotive Mechanics Conference, CERMA 2010
SP - 126
EP - 131
BT - Proceedings - 2010 IEEE Electronics, Robotics and Automotive Mechanics Conference, CERMA 2010
T2 - 2010 7th IEEE Electronics, Robotics and Automotive Mechanics Conference, CERMA 2010
Y2 - 28 September 2010 through 1 October 2010
ER -