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<div class="moz-cite-prefix">Dear Demetrio,<br>
<br>
You do not have to change variable types by yourself. This is what
the LP relaxation already does for you. The optimization problem
formulation that you enter to SCIP should contain the variable
types that you expect from any feasible solution, i.e.,
0/1-variables should be declared to be of binary type at the
creation time of your model.<br>
<br>
I recommend you to have a look at <a
href="http://scip.zib.de/doc/html/RELAX.php">How to Add
relaxation handlers</a> in the SCIP documentation, and base your
dynamic programming algorithm on the Relaxation handler interface.
The basic idea of a customized relaxation handler is that you may,
at each node, solve your own relaxation of the local node's
problem. You may use the data structures provided by the LP
relaxation as a starting point, only copy the relevant
constraints/rows, and apply your algorithm. If you do not intend
to solve node LP relaxations at all, you can set the lp/solvefreq
parameter to -1.<br>
<br>
Hope this helps,<br>
Gregor<br>
<br>
<br>
Am 23.10.2014 um 10:54 schrieb Demetrio Laganą:<br>
</div>
<blockquote
cite="mid:CA+n5bEJ9_Rv3wOCPLf=4GD2=JV-rD+J6rSo4VrK5zre9UgurrQ@mail.gmail.com"
type="cite">
<div dir="ltr">Dear SCIP list,
<div>I have a NonLinear 0/1 Programming problem modeled with
SCIP callable library. I need to use a continuous relaxation
of such a problem in a dynamic programming algorithm that
requires to solve it at each status by fixing some variables
to be binary and other to be equal to 1, moreover some
constraints belonging to the continuous relaxation must be
dropped and new constraints added progressively, as well as
the dynamic system progresses. I have look at the way to fix
to 1 some continuous variables through SCIPfix Var(), but I
don't know how to change the type of some continuous variables
to be binary(SCIP_VARTYPE_BINARY instead of
SCIP_VARTYPE_CONTINUOUS). Finally, I don't know how to drop o
make inactive some constraints in a given state of the dynamic
programming algortihm. Is there a way to do this without
clearing the model and re-create it at each status?</div>
<div>Thank you in advance</div>
<div>Regards</div>
<div>Demetrio Laganą<br>
<div><br>
</div>
</div>
</div>
<div class="gmail_extra"><br>
<div class="gmail_quote">2014-10-23 0:58 GMT+02:00 Gerald
Gamrath <span dir="ltr"><<a moz-do-not-send="true"
href="mailto:gamrath@zib.de" target="_blank">gamrath@zib.de</a>></span>:<br>
<blockquote class="gmail_quote" style="margin:0 0 0
.8ex;border-left:1px #ccc solid;padding-left:1ex">Dear
Andrea,<br>
<br>
in SCIP a rounding heuristic basically does the following:<br>
1) get the current LP solution<br>
2) round all fractional variables to an integer value<br>
3) check the resulting solution.<br>
<br>
How step 2 is performed influences the probability to find
feasible solutions and also the running time, that's why
there are multiple heuristics of this kind in SCIP.<br>
<br>
So you are right, no further LPs are solved by the
heuristic.<br>
<br>
If you want to fix some variables, then optimize the
resulting LP, fix again, solve the LP, and iterate until you
found an integer feasible solution, you should have a look
at the diving heuristics in SCIP, which all use this scheme.<br>
<br>
Best,<br>
Gerald<br>
<br>
<br>
Am 22.10.2014 um 19:04 schrieb Andrea Taverna:
<div class="HOEnZb">
<div class="h5"><br>
<blockquote class="gmail_quote" style="margin:0 0 0
.8ex;border-left:1px #ccc solid;padding-left:1ex">
Dear all,<br>
<br>
I'm a bit confused on how to implement a "rounding"
heuristic.<br>
<br>
I'm working on a column generation algorithm.<br>
Basically my heuristic fixes some fractional binary
variables to 0/1 by calling SCIPsetSolVal.<br>
<br>
What should I do after those fixings to get a feasible
solution?<br>
<br>
>From the examples, e.g. the TSP one, it seems that
no LP solver is called explicitly on the working copy
of the LP solution to generate a feasible solution .
There are just calls to functions like SCIPtrySol or
SCIProundSol.<br>
<br>
So, if I understand correctly, SCIP reoptimizes in
some way the working copy of the LP solution to obtain
the actual heuristic solution. Is that so?<br>
<br>
TIA<br>
<br>
Andrea<br>
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