Hello.
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.
Regards,
Andreas Klein.
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