Re: [ojAlgo-user] solving a linear optimization problem with ojAlgo ?

[Anders P. <an...@op...>]

If you you have 50 variables and several hundred equations there =20
typically is no feasible solution.

You can get a "best fit" solution using the QR or SVD decompositions =20
but those cannot handle the constraints/inequalities that the =20
variables must be non-negative. You'll have to invent something to =20
handle that.

/Anders

On 4 jan 2008, at 16.51, Andreas Andreakis wrote:

> hi,
>
> I want to find a solution to the following problem:
>
> (explained by example)
> 1 *c1 + 4 * c2 + 4* c3 + 4 * c4 =3D 2.5
> 1 *c1 + 4 * c2 + 1* c3 + 4 * c4 =3D 3.0
>
> here the constraints:
> 1) c1+c2+c3+c4 =3D 1 (of course this could be expressed as an =20
> additional equation: c1 + c2 + c3 + c4 =3D 1.0)
> 2) c1,c2,c3 and c4 are all positive
>
> Important is that I need only one and feasible solution, thus the =20
> computation should be as fast as possible. So there is no need to =20
> search for every possible result.
> And it needs to work with doubles (not only integers, because some =20
> libraries work only with integers)
>
> Actually the solution needs to scale for several dozens c=B4s ( there =20=

> will not be only 4 like c1,c2,c3,c4), but more like 50 c1, =20
> c2,...,c49, c50
> And there will not be only two equations (like in the example) but =20
> several hundred.
>
>
> So the questions are:
> 1) can I find a solution using ojAlgo ?
> 2) how will the performance be ?
> 3) could you give me a code snipped which is able to compute the =20
> given example ? (I will generalize it then myself)
>
> kind regards,
> Andreas
> ----------------------------------------------------------------------=20=

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