On Wed, Mar 26, 2008 at 1:17 PM, Andreas Klein <[EMAIL PROTECTED]> wrote: > I have some further problems with modelling an > optimization problem in R: > > How can I model some optimization problem in R with a > linear objective function with subject to some > nonlinear constraints? > I would like to use "optim" or "constrOptim", maybe > with respect to methods like "Simulated Annealing" or > "Sequential Quadric Programming" or something else, > which can solve the problem. But I have no idea how to > code in R! > > Example: > min (x1 + x2 + x3) > s.t. > p * (a*x1 + b*x2 + c*x3)^(-3) + (1-p) * (d*x1 + e*x2 + > f*x3)^(-3) >= g > > with a,b,c,d,e,f,g,p constant > 0 and x1,x2,x3 > 0 > also: a,b,c > d,e,f > > > I hope you can help me with some code for the above > problem so I can transfer it to my "real" problem. You > can also put some real numbers for the above problem. > I only wanted to abstract the problem with some > general constant.
I think that your optimization problem, Andreas, has no solution, but please correct me if I am wrong. In fact, when x1, x2 and x3 tend simultaneously to zero, the constrain is satisfied; the minimum would then be x1 = x2 = x3 = 0, but by your assumption, x1,x2,x3 > 0. Thus, the search for the minimum would be endless; no minimum exists. Paul ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
