simpleDE {adagio} | R Documentation |
Simple Differential Evolution Algorithm
Description
Simple Differential Evolution for Minimization.
Usage
simpleDE(fun, lower, upper, N = 64, nmax = 256, r = 0.4,
confined = TRUE, log = FALSE)
Arguments
fun |
the objective function to be minimized. |
lower |
vector of lower bounds for all coordinates. |
upper |
vector of upper bounds for all coordinates. |
N |
population size. |
nmax |
bound on the number of generations. |
r |
amplification factor. |
confined |
logical; stay confined within bounds. |
log |
logical; shall a trace be printed. |
Details
Evolutionary search to minimize a function: For points in the current generation, children are formed by taking a linear combination of parents, i.e., each member of the next generation has the form
where the are members of the current generation and
is an
amplification factor.
Value
List with the following components:
fmin |
function value at the minimum found. |
xmin |
numeric vector representing the minimum. |
nfeval |
number of function calls. |
Note
Original Mathematica version by Dirk Laurie in the SIAM textbook. Translated to R by Hans W Borchers.
Author(s)
HwB <hwborchers@googlemail.com>
References
Dirk Laurie. “A Complex Optimization". Chapter 5 In: F. Bornemann, D. Laurie, S. Wagon, and J. Waldvogel (Eds.). The SIAM 100-Digit Challenge. Society of Industrial and Applied Mathematics, 2004.
See Also
simpleEA
, DEoptim
in the ‘DEoptim’ package.
Examples
simpleDE(fnTrefethen, lower = c(-1,-1), upper = c(1,1))
# $fmin
# [1] -3.306869
# $xmin
# [1] -0.02440308 0.21061243 # this is the true global optimum!