how to implement parallel integer optimization with petsc?

Matthew Knepley knepley at mcs.anl.gov
Sat Feb 4 11:23:07 CST 2006


Tomasz Jankowski <tomjan at jay.au.poznan.pl> writes:

       PETSc basically offers parallel linear algebra and nonlinear solvers.
If you can phrase the algorithm in linear algebraic terms, then we can probably help.
In addition, it appears that you have a logically Cartesian space, so the DA object
could handle allocation, etc.

      Matt

> hello group
>
> because  i'm not sure what kind (MILP or IP) of optimization it is I attached short example at the end of this email
>
> my real problem is to find integer solution for matrix which is about 100X3500 large. I think it is good idea to do this
> task in parallel mode.
> I found yesterday PETSC pakage. It is incredible (for me), but compilation
> and testing proces has passed smooooth on my cluster (as much as 2x1PC :-)). Because of such painless implementation it
> would be great if icould use
> PETSC for solving my problem.
>
> my question is:
>
> is it posible with PETSC?
> if yes could you count(and shortly describe) consecutive steps?
> maybe someone already have done it?
>
> thank you for any replyes and sugesstions.
>
> tom
>
>
> ps. short example
> suposse we have two kinds of elements type A nad B which has such features like price.
> A1 200$
> A2 300$
> A3 400$
> B1 500$
> B2 600$
> B3 700$
> B4 900$
>
>
> we want to find set of pairs AxB which acomplish constrain for mean price. (when we make pair we sum prices of their
> elements)
> additionaly constrain is that we may use elements A only once and elements B only twice.
> so, our solution is binary matrix (1=make pair)like bellow
>    B1 B2 B3 B4 B5
> A1 1  0  0  0  0
> A2 1  0  0  0  0
> A3 0  1  0  0  0
>
>
> ########################################################
> #               tomjan at jay.au.poznan.pl                #
> #              jay.au.poznan.pl/~tomjan/               #
> ########################################################
>
>
>

-- 
"Failure has a thousand explanations. Success doesn't need one" -- Sir Alec Guiness




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