genopt: Genetic Optimization
In BurStMisc: Burns Statistics Miscellaneous

Description Usage Arguments Details Value References See Also Examples

Approximately minimizes the value of a function using a simple heuristic optimizer that uses a combination of genetic and simulated annealing optimization.

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  genopt(fun, population, lower = -Inf, upper = Inf,
         scale = dcontrol["eps"], add.args = NULL,
         control = genopt.control(...), ...)

`fun`	function that returns a numerical value.
`population`	a matrix or a list. If a matrix, then the rows correspond to the parameters and the columns are different parameter vectors. If a list, then it should have a component named "population" and optionally a component named "objective" – in particular, it can be the result of a call to `genopt`. If the "objective" component exists, then it is assumed to be the function values of the population and the function will not be evaluated on the members of the population.
`lower`	vector giving the lower bound for parameter values. This is replicated to be as long as the number of parameters.
`upper`	vector giving the upper bound for parameter values. This is replicated to be as long as the number of parameters.
`scale`	vector of scales to use when doing local search with a solution. This is replicated to be as long as the number of parameters.
`add.args`	list of additional arguments to `fun`.
`control`	an object like the output of `genopt.control` containing control parameters for the optimization.
`...`	arguments for `genopt.control` if the `control` argument is not given explicitly.

There is a summary method for class genopt which shows the call, a summary of the set of objectives found, and the best solution (set of parameters).

a list of class genopt with the following components:

`population`	a matrix of the same size as the input population matrix, but generally with different values in it.
`objective`	a vector with length equal to the number of columns of `population` containing the function value for the corresponding parameter vector in `population`.
`funevals`	the number of function evaluations performed. If `population` is given as a list that contains a "funevals" component, then that number is added to the number of evaluations done in the current call.
`random.seed`	the random seed at the start of the call – given so that you can reproduce the computations.
`call`	an image of the call that created this object.

The original version of this function appeared in "S Poetry".

genopt.control, summary.genopt.

  # two parameters, population size 5
  go1 <- genopt(function(x, other) sum(x, other),
                population=matrix(rexp(10), nrow=2, ncol=5),
                lower=0, add.arg=list(other=3), trace=FALSE)
  summary(go1)

  go2 <- genopt(function(x, other) sum(x, other), population=go1,
                lower=0, add.arg=list(other=3), trace=FALSE)