Description Usage Arguments Value Author(s) References Examples
View source: R/gRaviopt.Plot.R
visualisises the motion of the agents during the optimization process
1 | gRaviopt.Plot(fn, gRaviopt.Result, Par = 2, iterations = 200, n = 20, lower.limits = -10, upper.limits = 10, Movements = FALSE, Nice = TRUE, man.scaling = F, alpha = 0.1)
|
fn |
needs a 2D version of the function that is optimized with |
gRaviopt.Result |
graphical output |
Par |
number of parameters used. |
iterations |
number of iterations used for the optimization process |
n |
number of agents used for the optimization |
lower.limits |
the lower limits of the parameters used in "fn". |
upper.limits |
the upper limits of the parameters used in "fn". |
Movements |
should the movements be visualised or a static graphic of the optimized function |
Nice |
if |
man.scaling |
the user can specicify wether to choose the the radius of local optimization manually or automatically. |
alpha |
radius that divises between local and global optimization. |
either graphical output of the optimized function (usind persp
and image
) or the movements of the agents during the optimization process
Peter Kehler peter.kehler.jr@googlemail.com
A. Kaveh and S. Talatahari: A novel heuristic optimization method: charged system search, Acta Mech 213, 267–289 (2010)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ## Rastrigin02 function
## The function has a global maximum f(x) = 0 at the point (0,0).
## gRaviopt searches for maxima of the objective function between
## lower and upper bounds on each parameter to be optimized.
Rastrigin02 <- function(X){
-((X[,1]^2 - 10*cos(2*pi*X[,1]^2) + 10) + (X[,2]^2 - 10*cos(2*pi*X[,2]^2) + 10))
}
## This version of the function is needed for gRaviopt.Plot
Rastrigin02.2d <- function(x,y){
-((x*x - 10*cos(2*pi*x) + 10) + (y*y - 10*cos(2*pi*y) + 10))
}
# optimization process of Rastrigin02
Rast02 <- gRaviopt(fn= Rastrigin02, Par=2, n=20, lower.limits = -3, upper.limits = 3,man.scaling=TRUE,alpha=0.05)
# the best solutions found
Rast02$Memory
# the movements of the particles during the optimization process
gRaviopt.Plot(fn= Rastrigin02.2d, gRaviopt.Result=Rast02, Par=2, iterations=200, n=20, lower.limits = -3, upper.limits = 3, Movements=TRUE,man.scaling=TRUE,alpha=0.1,Nice=FALSE)
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