plot_caramel {caRamel} R Documentation

## Plotting of caRamel results

### Description

Plot graphs of the Pareto front and a graph of optimization evolution

### Usage

plot_caramel(caramel_results, nobj = NULL, objnames = NULL)


### Arguments

 caramel_results : list resulting from the caRamel() function, with fields $objectives and$save_crit nobj : number of objectives (optional) objnames : vector of objectives names (optional)

### Examples

# Definition of the test function
viennet <- function(i) {
val1 <- 0.5*(x[i,1]*x[i,1]+x[i,2]*x[i,2])+sin(x[i,1]*x[i,1]+x[i,2]*x[i,2])
val2 <- 15+(x[i,1]-x[i,2]+1)*(x[i,1]-x[i,2]+1)/27+(3*x[i,1]-2*x[i,2]+4)*(3*x[i,1]-2*x[i,2]+4)/8
val3 <- 1/(x[i,1]*x[i,1]+x[i,2]*x[i,2]+1) -1.1*exp(-(x[i,1]*x[i,1]+x[i,2]*x[i,2]))
return(c(val1,val2,val3))
}
nobj <- 3 # Number of objectives
nvar <- 2 # Number of variables
minmax <- c(FALSE, FALSE, FALSE) # All the objectives are to be minimized
bounds <- matrix(data = 1, nrow = nvar, ncol = 2) # Define the bound constraints
bounds[, 1] <- -3 * bounds[, 1]
bounds[, 2] <- 3 * bounds[, 2]

# Caramel optimization
results <- caRamel(nobj, nvar, minmax, bounds, viennet, popsize = 100, archsize = 100,
maxrun = 500, prec = matrix(1.e-3, nrow = 1, ncol = nobj), carallel = FALSE)

# Plot of results
plot_caramel(results)


[Package caRamel version 1.3 Index]