Description Usage Arguments Value See Also Examples
Adjust the mutated individuals to the required amount of turbines.
1 | trimton(mut, nturb, allparks, nGrids, trimForce, seed)
|
mut |
A binary matrix with the mutated individuals |
nturb |
A numeric value indicating the amount of required turbines |
allparks |
A data.frame consisting of all individuals of the current generation |
nGrids |
A numeric value indicating the total amount of grid cells |
trimForce |
If |
seed |
Set a seed for comparability. Default is NULL |
Returns a binary matrix with the correct amount of turbines per individual
Other Genetic Algorithm Functions:
crossover()
,
fitness()
,
genetic_algorithm()
,
init_population()
,
mutation()
,
selection()
,
windfarmGA()
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | ## Create a random rectangular shapefile
library(sf)
Polygon1 <- sf::st_as_sf(sf::st_sfc(
sf::st_polygon(list(cbind(
c(0, 0, 2000, 2000, 0),
c(0, 2000, 2000, 0, 0)))),
crs = 3035
))
## Create a uniform and unidirectional wind data.frame and plots the
## resulting wind rose
## Uniform wind speed and single wind direction
data.in <- as.data.frame(cbind(ws=12, wd=0))
## Calculate a Grid and an indexed data.frame with coordinates and grid cell Ids.
Grid1 <- grid_area(shape = Polygon1, size = 200, prop = 1);
Grid <- Grid1[[1]]
AmountGrids <- nrow(Grid)
startsel <- init_population(Grid,10,20);
wind <- as.data.frame(cbind(ws=12,wd=0))
wind <- list(wind, probab = 100)
fit <- fitness(selection = startsel, referenceHeight = 100, RotorHeight = 100,
SurfaceRoughness=0.3, Polygon = Polygon1, resol1 = 200, rot = 20,
dirspeed = wind, srtm_crop="", topograp=FALSE, cclRaster="")
allparks <- do.call("rbind", fit);
## SELECTION
## print the amount of Individuals selected.
## Check if the amount of Turbines is as requested.
selec6best <- selection(fit, Grid,2, TRUE, 6, "VAR");
selec6best <- selection(fit, Grid,2, TRUE, 6, "FIX");
selec6best <- selection(fit, Grid,4, FALSE, 6, "FIX");
## CROSSOVER
## u determines the amount of crossover points,
## crossPart determines the method used (Equal/Random),
## uplimit is the maximum allowed permutations
crossOut <- crossover(selec6best, 2, uplimit = 300, crossPart="RAN");
crossOut <- crossover(selec6best, 7, uplimit = 500, crossPart="RAN");
crossOut <- crossover(selec6best, 3, uplimit = 300, crossPart="EQU");
## MUTATION
## Variable Mutation Rate is activated if more than 2 individuals represent
## the current best solution.
mut <- mutation(a = crossOut, p = 0.3, NULL);
## TRIMTON
## After Crossover and Mutation, the amount of turbines in a windpark change and have to be
## corrected to the required amount of turbines.
mut1 <- trimton(mut = mut, nturb = 10, allparks = allparks, nGrids = AmountGrids,
trimForce = FALSE)
colSums(mut)
colSums(mut1)
|
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