[RBFOpt] run error

[Giacomo Nannicini]

Not knowing anything about the function, I can't make any comments
about convergence, unfortunately. If the function is well-behaved it
will converge in the limit. In practice, you just have to try and see.

G

On Wed, Apr 17, 2019 at 11:02 AM Damir Devetak <ddevetak at gmail.com> wrote:
>
> ok great; Just a sub-question. I want to optimize a black-box function with ~5 parameters with some par. being of different orders (x10). I didn't  read the paper that you referenced but how well can this algorithm converge in general?
>
> cheers, Damir
>
> On Wed, Apr 17, 2019 at 4:28 PM Giacomo Nannicini <giacomo.n at gmail.com> wrote:
>>
>> Hi Damir,
>> please read the installation instructions:
>> https://github.com/coin-or/rbfopt
>> You need to install bonmin and iptopt. Thanks.
>>
>> Giacomo
>>
>> On Wed, Apr 17, 2019 at 10:26 AM Damir Devetak <ddevetak at gmail.com> wrote:
>> >
>> >
>> >
>> >
>> > Hello,
>> >
>> >
>> > I began testing out the optimization package from git; the simple example of
>> >
>> > import rbfopt
>> > import numpy as np
>> > def obj_funct(x):
>> >   return x[0]*x[1] - x[2]
>> > ......
>> >
>> >
>> > gives,
>> >
>> >  Iter  Cycle  Action             Objective value      Time      Gap
>> >   ----  -----  ------             ---------------      ----      ---
>> >      0      0  Initialization           -0.782797      0.00   100.00 *
>> >      0      0  Initialization           59.515133      0.01   100.00
>> >      0      0  Initialization           20.000000      0.01   100.00
>> >      0      0  GlobalStep               -9.831245      0.05   100.00 *
>> >      1      0  GlobalStep                0.454536      0.08   100.00
>> >      2      0  GlobalStep               -9.933694      0.12   100.00 *
>> >      3      0  GlobalStep               -8.291156      0.16   100.00
>> >      4      0  GlobalStep               -9.988590      0.20   100.00 *
>> > Traceback (most recent call last):
>> >   File "test.py", line 25, in <module>
>> >     val, x, itercount, evalcount, fast_evalcount = alg.optimize()
>> >   File "/usr/lib/python2.7/site-packages/rbfopt/rbfopt_algorithm.py", line 749, in optimize
>> >     self.optimize_serial(pause_after_iters)
>> >   File "/usr/lib/python2.7/site-packages/rbfopt/rbfopt_algorithm.py", line 986, in optimize_serial
>> >     self.node_is_noisy)
>> >   File "/usr/lib/python2.7/site-packages/rbfopt/rbfopt_algorithm.py", line 2267, in local_step
>> >     node_pos[fmin_index])
>> >   File "/usr/lib/python2.7/site-packages/rbfopt/rbfopt_aux_problems.py", line 278, in minimize_rbf
>> >     if (not opt.available()):
>> >   File "/usr/lib64/python2.7/site-packages/pyomo/opt/base/solvers.py", line 99, in available
>> >     raise pyutilib.common.ApplicationError("Solver (%s) not available" % str(self.name))
>> > pyutilib.common._exceptions.ApplicationError: Solver (bonmin) not available
>> >
>> >
>> >
>> > Looking at version requires this is fine, any advice?
>> >
>> >
>> > cheers, Damir Devetak
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> > _______________________________________________
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