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<p class="MsoNormal">Hello,<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">I have a nonconvex optimization problem with ~300 unknowns, where the feasible set is "small" and the objective function relatively flat.<o:p></o:p></p>
<p class="MsoNormal"><span lang="DE-CH">I enter with an initial guess which is the best I can get reasonably, but which does not satisfy the constraints.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="DE-CH"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="DE-CH">IPOPT struggles, some cases are working fine, but with a high number of iterations and passing through several restauration phases; others do not work.<o:p></o:p></span></p>
<p class="MsoNormal">Using callbacks I observed that the constraints are not satisfied during a large number of iterations; they are satisfied only at the very end.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">I need to tune the IPOPT parameters, because I have a large number of "similar problems" to solve.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Any hints for a tuning strategy ?<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">I thought starting with the parameters relative to the "Initialization" phase, but I have no experience how to tune them.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Many thanks in advance,<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><span lang="DE-CH">--raoul<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="DE-CH"><o:p> </o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
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