[FlopCpp] Using "symbolic" variable names.
Christian Wolf
kalmar at uni-paderborn.de
Sat Nov 6 13:33:32 EDT 2010
Hello Marc,
Am 05.11.2010 17:55, schrieb marc.roth at rwe.com:
>
> Hi,
>
> I am developing a toy problem in order to figure out how FlopC++ has
> to be used. I consulted the example problems in the examples section
> to get started but have a couple of questions:
>
> 1) Use of symbolic names and LP file output: I would like to use the
> setName method on MP_variable, lets say, such as
>
> MP_model lp(new OsiCbcSolverInterface) ;
> MP_set T(123);
> MP_variable dispatch_period_volume(T);
> x.setName("dp_volume_");
>
> Once the model has been set up, I write the problem to a file, such as
>
> lp.attach();
> lp.Solver->writeLp("c:\\temp\\bmt);
>
> What I expect to see in the file bmt.lp is that the variable names are
> printed like dp_volume_1, dp_volume_2, ..., dp_volume_124, but what I
> get is only x1, ..., x124. Am I doing something wrong or is this
> feature not supported (in this case what is the
> MP_variable::setNames() method for?).
>
At the moment the feature is not yet supported, but it will be in the
near future, at least in the stochastic branch of FlopC++.
> 2) In the objective function in question some of the decision
> variables x are modelled by abs(x) (the absolute value of x).
> Obviously this is not a linear construct, but can be modelled as:
>
> x <= abs_x
> -1.0*x <= abs_x
> 0 <= abs_x
>
> Because I require various variables to be modelled as abs(.) I would
> like to implement a function that;
> A) creates the auxiliary variable(s) abs_x for each such x,
> B) adds above constraints/bounds to the model, and
> C) returns a MP_expression that can be added to the objective function
> expression in terms of the abs_x variables.
>
> I.e., I would like to delegate/encapsulate all issues to model the
> absolute value of a decision variable to a function.
>
> My initial approach, listed below, failed miserably because of the
> issue of automatic variables and copy constructors, etc., I guess
> boiling down to that FlopC++ elements are not "shallow" copied and
> reference counted on the one had and that MP_variables are not added
> to the model implicitly but only through their use in constraints and
> objective function. What is the proper way to accomplish this?
>
In my opinion this could work, if you work with pointers instead of
objects in your helper function. Create the MP_constraints and
MP_variables in the function with new, otherwise they should be lost
when the function goes out of scope. This is only a first thought about
the topic. I can look into it someday next week.
Hope this helps,
Christian
>
> static MP_expression
> lp_objective_absolute(
> MP_variable& x,
> MP_data& weight,
> MP_model& lp/*=MP_model::getDefaultModel()*/,
> const string& prefix/*="abs_"*/) {
> if (x.size() > 0) {
> if (x.getName().empty()) {
> string message;
> message += "decision variable(s) or affine expression(s) is/are not
> named";
> throw BmtException(message.c_str());
> }
> MP_set D(x.size());
> MP_variable abs_x(D);
> abs_x.setName(prefix + x.getName());
> abs_x.lowerLimit(D) = 0.0;
> MP_constraint abs_x_linctr_a(D);
> MP_constraint abs_x_linctr_b(D);
> abs_x_linctr_a(D) = x(D) <= abs_x(D);
> abs_x_linctr_b(D) = -1.0*x(D) <= abs_x(D);
>
> lp.add(abs_x_linctr_a);
> lp.add(abs_x_linctr_b);
>
> return sum(D, weight(D)*abs_x(D));
> } else {
> return MP_expression();
> }
> }
>
> And would be used such as
>
> MP_expression objective;
> MP_data UNIT_WEIGHT_X(T);
> UNIT_WEIGHT_X(T) = 1.0;
> objective = lp_objective_absolute(dispatch_period_volume,
> UNIT_WEIGHT_X, lp);
>
> Best Regards/Mit freundlichen Grüßen
> *Marc Roth*
> External Consultant,
> Structuring & Valuation
> Tel.: +41 55 534 44 82
> Mob: +44 7795 276 136
> Fax: +41 55 534 44 82
> _mailto:marc.roth at rwe.com_
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