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<div class="moz-cite-prefix">Nathan,<br>
<br>
For the original question. If the constraints are added to the
problem then the LP optimal answer will probably be different - in
dual values or primal values so the procedure may generate more
constraints.<br>
<br>
Doing multiple solves at root node (and cuts and heuristics) is
implemented in Cbc (idea due to Andrea Lodi , Matteo Fischetti ,
Michele Monaci , Domenico Salvagnini and Andrea Tramontani). If
you set multipleRootPasses then your cut generator will be called
with different starting solutions (if at all degenerate) and
different pseudo random seeds.<br>
<br>
John Forrest<br>
<br>
On 08/09/17 13:11, Nathan Petty wrote:<br>
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<div dir="ltr">As a follow on question, if the answer to the
original question is that there is indeed a starting condition
that will result in the solution path being the same in multiple
runs, is there also then a starting condition seed that will
guarantee a different path? This would also be very helpful
because I could start multiple solvers with different seeds in
order to generate a family of optimal paths.</div>
<div class="gmail_extra"><br>
<div class="gmail_quote">On Thu, Sep 7, 2017 at 1:39 PM, Nathan
Petty <span dir="ltr"><<a
href="mailto:nathanlpetty@gmail.com" target="_blank"
moz-do-not-send="true">nathanlpetty@gmail.com</a>></span>
wrote:<br>
<blockquote class="gmail_quote">I am solving a TSP problem
using CBC(2.9.9) and I have built a subtour<br>
elimination procedure that adds subtour busting constraints
and<br>
resolves. It keeps adding these subtour elim constrains
until the<br>
solver finds a feasible optimal solution.<br>
<br>
I save these subtour constraints in my database so that when
I<br>
resolve, they are loaded into the initial formulation, and I
should in<br>
theory not run into any more subtours because after all, it
just found<br>
an optimal feasible using this set of constraints. But, to
my<br>
surprise, the solver finds more subtours (albiet many fewer
than the<br>
first time). incase it matters, every variable has a unique<br>
coefficient (driven my euclidean distance) in my obj
function, so<br>
there's a nice gradient there to slide on.<br>
<br>
So there is something pseudo non-deterministic about the
solution path<br>
and my gut feeling is that it might be related to a starting<br>
condition/initial solution? So, is there a way to control
that<br>
starting condition? Is it due to something else I am not
thinking<br>
about?<br>
<br>
Thanks,<br>
Nathan Petty<br>
</blockquote>
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