Hi Jude, You may get an answer here, but if you don't soon, check on the julia-opt google group.
Cheers, Kevin On Wednesday, September 10, 2014, Jude <[email protected]> wrote: > Hi, > > In my model I iterate over a lot of different values and solve a > constrained optimisation problem but for some values of my lower and upper > bounds I get an error saying "invalid NLopt arguments". I am not sure why > as my lower bound is < upper bound in all the iterations. I tried to > understand this using a more simple example such as the following but even > for this simple example if I set the bounds to (1,100) it's fine but if I > use (2,100) I get the same error. Why is this?: > > using NLopt > function simpleopt(lbA1, ubA1) > > z=1 > > function test_max(x,z) > x[1]^2 + z > end > > count = 0 > > function func(x::Vector, grad::Vector) > global count +=1 > println("f_$count($x)") > test_max(x[1],z) > end > > opt = Opt(:LN_SBPLX,1) > lower_bounds!(opt, [lbA1]) > upper_bounds!(opt, [ubA1]) > min_objective!(opt, func) > > (minf,minx,ret)=optimize(opt,[1]) > > println("got $minf at $minx after $count iterations (returned $ret)") > end >
