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<p style="margin-top:0;margin-bottom:0">Hi Gregor,</p>
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<p style="margin-top:0;margin-bottom:0">Thank you for your helpful suggestions for adjusting the branching priority and/or branching factors. I look forward to trying them out.</p>
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<p style="margin-top:0;margin-bottom:0">- Rich </p>
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<div id="divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" style="font-size:11pt" color="#000000"><b>From:</b> Scip <scip-bounces@zib.de> on behalf of Gregor Hendel <hendel@zib.de><br>
<b>Sent:</b> Sunday, May 5, 2019 4:50:56 PM<br>
<b>To:</b> scip@zib.de<br>
<b>Subject:</b> Re: [SCIP] Dependent variables?</font>
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<div style="background-color:#FFFFFF">Good morning Richard and list,<br>
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you have two possibilities to tell SCIP which variables should be prioritized (branched on/assigned first in the tree).<br>
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1. The hard way: Assign a higher <b>branching priority</b> (SCIPvarChgBranchPriority()) to some variables. All branching rules and some of the primal heuristics will only consider fractional branching candidates that have the highest priority. Lower priority
variables are excluded from the branching decision until there is no high priority variable left. The default priority of all variables is 0. Since the priority is an integer attribute of a variable, you can in principle fix the variable order for SCIP to
branch on, by assigning unique priorities to every variable.<br>
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2. The soft way: Assign a higher <b>branching factor</b> (SCIPvarChgBranchFactor()) to fine-tune the scoring mechanism. If your s variables (start times) have a branching priority of 10.0 (the default is 1.0, of course), they are much more likely to be selected
for branching, unless the (unweighted) branching score of another variable (say, a job end variable e) is 10 times higher than that of the best s variable.<br>
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Branching enthusiasts may even mix 1. and 2. Let us know if you experience a good impact with one of the above methods.<br>
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Happy branching,<br>
Gregor<br>
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<div class="x_moz-cite-prefix">Am 03.05.19 um 18:51 schrieb Levinson, Richard J. (ARC-TI)[SGT, INC]:<br>
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<div id="x_divtagdefaultwrapper" dir="ltr" style=""><span><span style="">Hello,</span></span></div>
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<div id="x_divtagdefaultwrapper" dir="ltr" style=""><span><span style="">I'm looking for a way to specify that some variables are the "primary" decision variables to drive search, while other variables are "dependent" variables, which</span><span style=""> depend
on the primary variables via constraints, so that the dependent variable assignments are made only after feasible assignments for the primary variables have been found. </span><br>
<span style=""></span></span></div>
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<div id="x_divtagdefaultwrapper" dir="ltr" style=""><span style="font-size:12pt">Is there a way to tell SCIP </span><span style="font-size:12pt">that some variables are considered ‘dependent’, i.e. they should not be considered as part of the search space,
but must be propagated using constraints in the problem?</span><br>
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<p style="margin-top:0; margin-bottom:0">Or if there is no way to specify that some variables should not be part of the search space, is there an option to specify the order/priority for assigning variables? So the solver<span style="font-size:12pt"> searches
first through the domains of the primary (high priority) variables to find a feasible solution before it searches for consistent assignments for the dependent variables. </span><span style="font-size:12pt"></span></p>
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<p style="margin-top:0; margin-bottom:0">For example, we may have variables s, e, d, representing a job's start, end, and duration times, and we want to first search for feasible assignments for s and e before applying the constraint that e-s = d. </p>
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<p style="margin-top:0; margin-bottom:0">Thank you,</p>
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<p style="margin-top:0; margin-bottom:0"> Rich Levinson</p>
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