Re: Constrained Nonlinear Optimization problem

[Ben Abbott]

On May 2, 2014, at 8:33 PM, Ether Jones <address@hidden> wrote:

> On Fri, May 2, 2014 at 8:10 PM, Ben Abbott <address@hidden> wrote:
>> On May 2, 2014, at 7:40 PM, Ether Jones <address@hidden> wrote:
>> 
>> >
>> > Could someone please show me how to set up this problem in Octave?
>> >
>> > Maximize (x + y)
>> >
>> > Subject to constraints:
>> >
>> > 0 <= x <= 75
>> >
>> > 0 <= y <= 75
>> >
>> > 29.5 - sqrt(0.184*(x+y)^2 + x^2) >= 0.0
>> >
>> > 45.5 - sqrt(0.184*(x+y)^2 + y^2) >= 0.0
>> >
>> >
>> > I have solved it with Maxima, Python, AMPL, and Excel and get the 
>> > following answer:
>> >
>> > x = 17.2
>> >
>> > y = 38.7
>> >
>> > But I'm having trouble setting it up in Octave
>> >
>> > Thank you.
>> 
>> I'd use the sqp() function. The documentation is at the link below.
>> 
>> https://www.gnu.org/software/octave/doc/interpreter/Nonlinear-Programming.html
>> 
>> You'll need to convert to a minimization problem.
>> 
>> Ben
> 
> My fault for not being clearer in my original post.
> 
> I'm aware of Octave's sqp() function.  I have read the sqp() entry in the 
> manual.  I am having difficulty figuring out how to convert/transform/setup 
> my problem so that I can use the sqp() function.
> 
> Can you help with that?
> 
> Thank you.

Please don't reply above (called top-posting), Instead reply at the bottom 
(bottom-posting) so that those who arrive later can follow along. Also be sure 
to "reply-all" so that the entire conversation makes it into the archive.

The only tricky part is converting your maximization function into a 
minimization function.  "maximize f([x,y])" is equivalent to "minimize 
-f([x,y])".

If you have difficulty with Octave's syntax, please be specific about what 
you're having difficulty with.

Ben