genopt.control: Control parameters for genopt
In BurStMisc: Burns Statistics Miscellaneous

Description Usage Arguments Value See Also Examples

Returns a list suitable as the control argument of the genopt function.

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  genopt.control(births = 100, random.n = 0, jitters.n = 3,
                 trace = TRUE, eps = 0.1, prob = 0.4, scale.min = 1e-12,
                 maxeval = Inf)

`births`	the number of times two parents are combined to create a new solution.
`random.n`	the number of random solutions created (and evaluated) before the genetic phase starts.
`jitters.n`	the number of times a newly successful solution is changed (in the simulated annealing phase) in an attempt to find a nearby better one.
`trace`	logical value: should progress be printed?
`eps`	the default value for the scale of the jittering in simulated annealing.
`prob`	in the selection of parameters between two parents, the probability of each coming from the first parent.
`scale.min`	the minimum value allowed in the `scale` argument of `genopt`.
`maxeval`	the maximum number of function evaluations allowed. This takes previous function calls into account if `funevals` is a component of the `population` argument of `genopt`.

a list with components:

`icontrol`	vector of the control parameters that are logically integer (or logical).
`dcontrol`	vector of the control parameters that are logically real-valued.

genopt.

  goc1 <- genopt.control(random.n=200, births=1000, trace=FALSE)

  go1 <- genopt(function(x, other) sum(x, other),
                matrix(rexp(10), nrow=2, ncol=5), lower=0, add.arg=list(other=3),
                control=goc1)

  goc2 <- genopt.control(random.n=0, births=1000, trace=FALSE)

  go2 <- genopt(function(x, other) sum(x, other), go1,
                lower=0, add.arg=list(other=3), control=goc2)