<br><font size=2 face="sans-serif">Kyle,</font>
<br>
<br><font size=2 face="sans-serif">It would should improve the time giving
it a good feasible solution. If you create a solution in an array
numberColumns long you can pass it to Clp using setColSolution(array).
If you want to save memory and are careful you can get Clp's solution
array by model->primalColumnSolution() and fill it in directly.</font>
<br>
<br><font size=2 face="sans-serif">To use you then call primal(1) instead
of primal().</font>
<br>
<br><font size=2 face="sans-serif">The code should then go through matrix
once and the number of iterations should be the number of variables not
at their bounds. You will get a message something like "end
of values pass". These iterations can be very fast. At
this stage you should have a basic feasible solution and primal will continue
as normal. If this looks promising but the values pass is taking
too much time you can improve things by putting variables in basis to start
with but try the simple approach first.</font>
<br>
<br><font size=2 face="sans-serif">BTW did you understand my note of the
thirteenth to you suggesting a "sprint" strategy. It may
have been a bit garbled but if your problem is very large and very long
and thin then it can work very well.</font>
<br>
<br><font size=2 face="sans-serif">John Forrest</font>
<br>
<br>
<br>
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<td width=40%><font size=1 face="sans-serif"><b>Kyle Ellrott <kellrott@csbl.bmb.uga.edu></b>
</font>
<br><font size=1 face="sans-serif">Sent by: coin-lpsolver-bounces@list.coin-or.org</font>
<p><font size=1 face="sans-serif">03/18/2005 11:10 AM</font>
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<div align=right><font size=1 face="sans-serif">To</font></div>
<td valign=top><font size=1 face="sans-serif">coin-lpsolver@list.coin-or.org</font>
<tr>
<td>
<div align=right><font size=1 face="sans-serif">cc</font></div>
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<tr>
<td>
<div align=right><font size=1 face="sans-serif">Subject</font></div>
<td valign=top><font size=1 face="sans-serif">[Coin-lpsolver] Problem start
position</font></table>
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<td></table>
<br></table>
<br>
<br>
<br><font size=2><tt>I'm still trying to get a handle on some of the technical
details in <br>
linear programming, so please excuse me if this question is out <br>
there...<br>
<br>
From what I under stand, simplex works by moving from vertex to vertex
<br>
of possible solutions, until it finds the optimal one. I was <br>
wondering, if I could produce a feasible answer (with dynamic <br>
programming), that is close to the optimal point (and would have been <br>
optimal save for some additional complexities added to the problem, <br>
which is why I'm using integer programming and not dynamic), could I <br>
use that as a start point in the search? Would this improve the speed
<br>
of the algorithm? And if it is possible, how would I go about <br>
initializing CLP with this information?<br>
<br>
<br>
Kyle<br>
<br>
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</tt></font>
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