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<div>Hi,</div>
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<div>i wrote a small Python-based library to use Bonmin as MIQP-solver (not much non-commercial alternative solvers). </div>
<div>After writing an interface for cvxpy's newly introduced QP-reduction pipeline (convex only), i observed the following:</div>
<div> </div>
<div>
<div>
<div> x = Variable()<br/>
y = Variable(integer=True)<br/>
z = Variable(boolean=True)</div>
<div> constraints = [0 <= x, x <=5,<br/>
-3 <= y, y <=2,<br/>
0 <= z, z <= 1] # !!! imho: should not be needed</div>
<div> p = Problem(Maximize(x + y + z), constraints)<br/>
p.solve(solver='BONMIN_QP', verbose=True)<br/>
assert p.status == s.OPTIMAL</div>
<div> </div>
</div>
<div>does only work, if i manually add constraints to induce bounds on z, which is of boolean-type!</div>
<div>So removing the last line of the two constraints bounding z, Bonmin results in the final result: unbounded!</div>
<div>The relaxation should also be more strong when those bounds are available.</div>
<div> </div>
<div>I was expecting Bonmin to automatically introduce those bounds when relaxing the problem</div>
<div>after observing some of those variables are binary (bound-information implicitly given).</div>
<div> </div>
<div>I don't think i did something wrong in providing variable-type options within my wrapper.</div>
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<div><u>Is this by design? Is this a bug? Or do you think i made a mistake?</u></div>
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<div>It should not matter, but if someone is interested, the links:</div>
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<div>python-lib wrapping Bonmin and doing necessary Jac/Hess calcs:</div>
<div>- <a href="https://deref-web-02.de/mail/client/f1vAKS3sel8/dereferrer/?redirectUrl=https%3A%2F%2Fgithub.com%2Fsschnug%2FpyMIQP" target="_blank">https://github.com/sschnug/pyMIQP</a></div>
<div> </div>
<div>cvxpy-interface:</div>
<div>- <a href="https://deref-web-02.de/mail/client/LXHNEdkuygw/dereferrer/?redirectUrl=https%3A%2F%2Fgithub.com%2Fcvxgrp%2Fcvxpy%2Fpull%2F438" target="_blank">https://github.com/cvxgrp/cvxpy/pull/438</a></div>
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<div>Greetings,</div>
<div>Sascha</div>
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