Hellooooooooooooooooooooooooooooo !!! > Thanks! I spent some time with the graph and milp support today, and it's > exactly what I was looking for.
Glad to hear it ! :-) > Do you have an idea of how the current > implementations scale with the size of the graph? Oh. Well, I do not use LP to solve problems on huge graphs. But I do solve huge LP for small graphs :-) > Any interest in adding > support for parallel algorithms? Oh. Well, I guess no one -- least of all me -- would mind. Which kind of algorithms would you have in mind ? :-) > I'm interested in the underlying data > structures for the graphs and how the objective function expressions are > being passed to the low level implementations (e.g. Coin) Well, I hope that I did the job well on this respect. We use all the solvers through their C/C++ Api, and at this level the functions are given as efficiently a the solvers let us do it, that is something like 2 C arrays (the indices of the variables which have a nonzero coefficient, and the list of coefficients), or through methods for sparse vectors (I think only CBC does that). Of course, when you use the LP classes at Python level, we first have to do some Python operations to convert the information you give to the format the solvers expect, but at least we have control on all levels down to C. So we are more or less free to do as we want :-) One thing to note : when you have to sum MANY variables, pleaaaaaase do not use sum([ x for x in the_variables_i_want_to_add_together]). There is a Sum function made just for that. It is a pity I had to do such things, but otherwise adding n variables together result in a n^2 algorithm, while linear time should be sufficient :-D This function is available this way : from sage.numerical.mip impot Sum And all the LP codes available in Sage use this Sum function instead of the usual "sum" :-) Anyway, the code you are interestedin is defined in sage/numerical/mip. The sums/comparisons between MILP variables are implemented in the MIPVariable and LinearFunction classes you will find at the bottom of the file, and you will also be interested by the add_constraint method, and the solver-specific add_linear_constraint functions in the sage/numerical/mip/backend_* files. Nathann -- To post to this group, send email to sage-support@googlegroups.com To unsubscribe from this group, send email to sage-support+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/sage-support URL: http://www.sagemath.org
