[R] DE optimization with equality constraint

[Hans W. Borchers]

> Reply to "Optimization with constraint" on March 14, 2008

One can get an accurate solutons applying the "Differential Evolution" algorithm
as implemented in the DEoptim package:

    f2 <- function(x){
        if (x[1] + x[2] < 1 || x[1] + x[2] > 1) {
            r <- Inf
        } else {
            r <- x[1]^2 + x[2]^2
        }
        return(r)
    }

    lower <- c(0, 0)
    upper <- c(1, 1)

    DEoptim(f2, lower, upper, control=list(refresh=200))$bestmem

    iteration:  200 best member:  0.5 0.5 best value:  0.5

This approach assumes nothing about the gradient, hessian or whatever. And the
equality is split into two inequalities assuming no relaxation or penalty.


Andreas Klein <klein82517 <at> yahoo.de> wrote:
> 
> Hello.
> 
> I have some problems, when I try to model an
> optimization problem with some constraints.
> 
> The original problem cannot be solved analytically, so
> I have to use routines like "Simulated Annealing" or
> "Sequential Quadric Programming".
> 
> But to see how all this works in R, I would like to
> start with some simple problem to get to know the
> basics:
> 
> The Problem:
> min f(x1,x2)= (x1)^2 + (x2)^2
> s.t. x1 + x2 = 1
> 
> The analytical solution:
> x1 = 0.5
> x2 = 0.5
> 
> Does someone have some suggestions how to model it in
> R with the given functions optim or constrOptim with
> respect to the routines "SANN" or "SQP" to obtain the
> analytical solutions numerically?
> 
> Again, the simple example should only show me the
> basic working of the complex functions in R.
> 
> Hope you can help me.
> 
> With regards
> Andreas.