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<div style="direction: ltr;font-family: Tahoma;color: #000000;font-size: 10pt;">Thanks Gerald, this was helpful indeed.
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<div>Regards,</div>
<div>Ahmed<br>
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<div id="divRpF845511" style="direction: ltr;"><font face="Tahoma" size="2" color="#000000"><b>From:</b> Scip [scip-bounces@zib.de] on behalf of Gerald Gamrath [gamrath@zib.de]<br>
<b>Sent:</b> Monday, February 01, 2016 5:53 AM<br>
<b>To:</b> scip@zib.de<br>
<b>Subject:</b> Re: [SCIP] Heuristics Characters<br>
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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" target="_blank">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>
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<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>
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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>
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<div>Regards,</div>
<div>Ahmed</div>
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