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<div class="moz-cite-prefix">Dear Ahmed,<br>
<br>
I guess you cannot print the primal heuristics via the opti
toolbox, but you could just start the SCIP binary for once and
print them.<br>
<br>
There is no list like this in the documentation, but you can have
a look at<br>
<a class="moz-txt-link-freetext" href="http://scip.zib.de/doc/html_devel/group__PRIMALHEURISTICS.php">http://scip.zib.de/doc/html_devel/group__PRIMALHEURISTICS.php</a><br>
where all primal heuristics are listed. Since this is the
developers manual, you can also see the corresponding .c files
after two clicks (one on the heuristic, one for the definition of
the SCIPincludeHeur...() method, where the .c file is referenced).
There, one of the first lines is <span class="lineno"></span><span
class="preprocessor"></span><span class="preprocessor">#define
HEUR_DISPCHAR, followed by the caracter.<br>
<br>
Anyway, below is the current list of heuristics for SCIP 3.2.<br>
<br>
Best,<br>
Gerald<br>
<br>
<tt> primal heuristic c priority freq ofs description</tt><tt><br>
</tt><tt> ---------------- - -------- ---- --- -----------</tt><tt><br>
</tt><tt> ofins A 60000 -1 0 primal
heuristic for reoptimization, objective function induced
neighborhood search</tt><tt><br>
</tt><tt> trivialnegation j 40000 -1 0 negate
solution entries if an objective coefficient changes the sign,
enters or leaves the objective.</tt><tt><br>
</tt><tt> reoptsols J 40000 -1 0 primal
heuristic updating solutions found in a previous optimization
round</tt><tt><br>
</tt><tt> trivial t 10000 0 0 start
heuristic which tries some trivial solutions</tt><tt><br>
</tt><tt> shiftandpropagate T 1000 0 0 Pre-root
heuristic to expand an auxiliary branch-and-bound tree and
apply propagation techniques</tt><tt><br>
</tt><tt> zeroobj Z 100 -1 0 heuristic
trying to solve the problem without objective</tt><tt><br>
</tt><tt> simplerounding r 0 1 0 simple and
fast LP rounding heuristic</tt><tt><br>
</tt><tt> dualval Y 0 -1 0 primal
heuristic using dual values</tt><tt><br>
</tt><tt> randrounding G -200 20 0 fast LP
rounding heuristic</tt><tt><br>
</tt><tt> zirounding z -500 1 0 LP rounding
heuristic as suggested by C. Wallace taking row slacks and
bounds into account</tt><tt><br>
</tt><tt> rounding R -1000 1 0 LP rounding
heuristic with infeasibility recovering</tt><tt><br>
</tt><tt> shifting s -5000 10 0 LP rounding
heuristic with infeasibility recovering also using continuous
variables</tt><tt><br>
</tt><tt> intshifting i -10000 10 0 LP rounding
heuristic with infeasibility recovering and final LP solving</tt><tt><br>
</tt><tt> oneopt b -20000 1 0 1-opt
heuristic which tries to improve setting of single integer
variables</tt><tt><br>
</tt><tt> twoopt B -20100 -1 0 primal
heuristic to improve incumbent solution by flipping pairs of
variables</tt><tt><br>
</tt><tt> indicator A -20200 1 0 indicator
heuristic to create feasible solutions from values for
indicator variables</tt><tt><br>
</tt><tt> fixandinfer I -500000 -1 0 iteratively
fixes variables and propagates inferences</tt><tt><br>
</tt><tt> feaspump F -1000000 20 0 objective
feasibility pump 2.0</tt><tt><br>
</tt><tt> clique Q -1000500 -1 0 LNS
heuristic using a clique partition to restrict the search
neighborhood</tt><tt><br>
</tt><tt> coefdiving c -1001000 10 1 LP diving
heuristic that chooses fixings w.r.t. the matrix coefficients</tt><tt><br>
</tt><tt> pscostdiving p -1002000 10 2 LP diving
heuristic that chooses fixings w.r.t. the pseudo cost values</tt><tt><br>
</tt><tt> fracdiving f -1003000 10 3 LP diving
heuristic that chooses fixings w.r.t. the fractionalities</tt><tt><br>
</tt><tt> nlpdiving d -1003000 10 3 NLP diving
heuristic that chooses fixings w.r.t. the fractionalities</tt><tt><br>
</tt><tt> veclendiving v -1003100 10 4 LP diving
heuristic that rounds variables with long column vectors</tt><tt><br>
</tt><tt> distributiondiving e -1003300 10 3 Diving
heuristic that chooses fixings w.r.t. changes in the solution
density</tt><tt><br>
</tt><tt> intdiving n -1003500 -1 9 LP diving
heuristic that fixes binary variables with large LP value to
one</tt><tt><br>
</tt><tt> actconsdiving a -1003700 -1 5 LP diving
heuristic that chooses fixings w.r.t. the active constraints</tt><tt><br>
</tt><tt> objpscostdiving o -1004000 20 4 LP diving
heuristic that changes variable's objective values instead of
bounds, using pseudo costs as guide</tt><tt><br>
</tt><tt> rootsoldiving S -1005000 20 5 LP diving
heuristic that changes variable's objective values using root
LP solution as guide</tt><tt><br>
</tt><tt> linesearchdiving l -1006000 10 6 LP diving
heuristic that chooses fixings following the line from root
solution to current solution</tt><tt><br>
</tt><tt> guideddiving g -1007000 10 7 LP diving
heuristic that chooses fixings in direction of incumbent
solutions</tt><tt><br>
</tt><tt> octane O -1008000 -1 0 octane
primal heuristic for pure {0;1}-problems based on Balas et al.</tt><tt><br>
</tt><tt> rens E -1100000 0 0 LNS
exploring fractional neighborhood of relaxation's optimum</tt><tt><br>
</tt><tt> rins N -1101000 25 0 relaxation
induced neighborhood search by Danna, Rothberg, and Le Pape</tt><tt><br>
</tt><tt> localbranching L -1102000 -1 0 local
branching heuristic by Fischetti and Lodi</tt><tt><br>
</tt><tt> mutation M -1103000 -1 8 mutation
heuristic randomly fixing variables</tt><tt><br>
</tt><tt> crossover C -1104000 30 0 LNS
heuristic that fixes all variables that are identic in a
couple of solutions</tt><tt><br>
</tt><tt> dins D -1105000 -1 0 distance
induced neighborhood search by Ghosh</tt><tt><br>
</tt><tt> vbounds V -1106000 -1 0 LNS
heuristic uses the variable lower and upper bounds to
determine the search neighborhood</tt><tt><br>
</tt><tt> bound H -1107000 -1 0 heuristic
which fixes all integer variables to a bound and solves the
remaining LP</tt><tt><br>
</tt><tt> undercover U -1110000 0 0 solves a
sub-CIP determined by a set covering approach</tt><tt><br>
</tt><tt> proximity P -2000000 -1 0 heuristic
trying to improve the incumbent by an auxiliary proximity
objective function</tt><tt><br>
</tt><tt> subnlp q -2000000 1 0 primal
heuristic that performs a local search in an NLP after fixing
integer variables and presolving</tt><tt><br>
</tt><tt> trysol y -3000000 1 0 try solution
heuristic</tt><br>
</span><br>
On 31.01.2016 20:04, Ahmed Ibrahim wrote:<br>
</div>
<blockquote
cite="mid:7BE9AA462EB7354CAA5256EB22A6A0DCB8ADFF81@UMCE3EXMD01.ad.umanitoba.ca"
type="cite">
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<div style="direction: ltr;font-family: Tahoma;color:
#000000;font-size: 10pt;">Hi All,
<div>Is there any way I could know get a list of the primal
heuristics of scip and their display characters other than the
"display heuristics" command in the interactive shell? I'm
using the Matlab interface "opti toolbox" so I don't know
whether I have the option of using this command or not. Is
there a list of those in the documentation somewhere?</div>
<div><br>
</div>
<div>Regards,</div>
<div>Ahmed</div>
</div>
<br>
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