Permutation optimization with gaoptim package
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My recent update of GAPerm
, which can be used to perform combinatorial optimization using the Genetic Algorithm approach.
The example below solves a TSP instance with 10 points around a circumference, then plots the results.
Enjoy it!
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# TSP with 10 cities around a circular pattern | |
require(gaoptim) | |
op <- par(mfrow = c(2, 1)) | |
n = 10 | |
R = 10 | |
angs = seq(0, 2*pi, length = n) | |
xp = R * cos(angs) + rnorm(n) | |
yp = R * sin(angs) + rnorm(n) | |
xp = c(xp, xp[1]) | |
yp = c(yp, yp[1]) | |
base.M = matrix(c(xp, yp), ncol = 2) | |
dist.FUN = function(p) | |
{ | |
p = c(p, p[1]) | |
M.diff = diff(base.M[p, ]) | |
dists = apply(M.diff, 1, function(x)x[1]^2 + x[2]^2) | |
1/sum(dists) | |
} | |
ga1 = GAPerm(dist.FUN, n, popSize = 100, mutRate = 0.3) | |
ga1$evolve(100) | |
plot(ga1) | |
plot(xp, yp, type = 'n', xlab = '', ylab = '', main = 'Best Tour') | |
res = ga1$bestIndividual() | |
res = c(res, res[1]) | |
i = 1:n | |
xi = base.M[res[i], 1] | |
yi = base.M[res[i], 2] | |
xf = base.M[res[i + 1], 1] | |
yf = base.M[res[i + 1], 2] | |
arrows(xi, yi, xf, yf, col = 'red', angle = 10) | |
text(base.M[res, 1], base.M[res, 2], 1:n, cex = 0.9, col = 'gray20') | |
par(op) |
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