Thanks, I'll do that so.
On Wednesday, September 10, 2014 5:11:22 PM UTC+1, Kevin Squire wrote: > > 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] <javascript:>> > 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 >> >
