aylmer (version 1.0-1)

best: Optimize a board using simulated annealing

Description

Uses simulated annealing to find the `best' permissible board, using any objective function

Usage

best(x, func = NULL, n = 100, ...)

Arguments

x

A board

func

The objective function, with default NULL meaning to use -prob(x)

n

Maximum number of attempts (passed to candidate())

...

Further arguments passed to optim()

Details

The help page for optim() gives an example of simulated annealing being used to solve the travelling salesman problem and best() uses the same technique in which the gr argument specifies a function used to generate a new candidate point (candidate()).

See Also

optim,prob

Examples

a <- matrix(0,5,5)
 diag(a) <- NA
 a[cbind(1:5 , c(2:5,1))] <- 4
 best(a,control=list(maxit=10))   ## Answer should be all ones except the diagonal


# Now a non-default function; SANN should be able to get func(x) down to
#  zero pretty quickly:

 best(a,func=function(x){x[1,2]},control=list(maxit=100))