<div dir="ltr"><div><div><div>Hello,<br><br></div>Make sure that you use warm start and that you tune the warm-start options. <br>After the first NLP is solved the following solutions should be close to the previous ones:<br><a href="https://www.coin-or.org/Ipopt/documentation/node49.html">https://www.coin-or.org/Ipopt/documentation/node49.html</a><br><br></div>Best regards,<br></div>João Rui Leal<br></div><div class="gmail_extra"><br><div class="gmail_quote">2017-01-10 5:12 GMT+00:00 Jonathan Currie <span dir="ltr"><<a href="mailto:jonathan.currie@aut.ac.nz" target="_blank">jonathan.currie@aut.ac.nz</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">












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<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext">Hi,<u></u><u></u></span></p>

<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext"><u></u> <u></u></span></p>

<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext">OPTI Toolbox supplies the MKL PARDISO version, thus I’ve added the option to the ipoptset() interface so it can be used. This is

 in the OPTI Toolbox development branch on Github, or simply replace your ipoptset.m with the file below:<u></u><u></u></span></p>

<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext"><a href="https://github.com/jonathancurrie/OPTI/blob/Development/Utilities/opti/ipoptset.m" target="_blank">https://github.com/<wbr>jonathancurrie/OPTI/blob/<wbr>Development/Utilities/opti/<wbr>ipoptset.m</a><u></u><u></u></span></p>

<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext"><u></u> <u></u></span></p>

<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext">Use via:<u></u><u></u></span></p>

<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext">ipoptOpts = ipoptset('pardiso_redo_<wbr>symbolic_fact_only_if_inertia_<wbr>wrong','yes');<u></u><u></u></span></p>

<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext">opts = optiset(‘solverOpts’,<wbr>ipoptOpts);<u></u><u></u></span></p>

<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext">%etc…<u></u><u></u></span></p>

<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext"><u></u> <u></u></span></p>

<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext">Cheers,<u></u><u></u></span></p>

<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext">Jonathan<u></u><u></u></span></p>

<p class="MsoNormal"><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext"><u></u> <u></u></span></p>

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<p class="MsoNormal"><b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext" lang="EN-US">From:</span></b><span style="font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext" lang="EN-US"> Ipopt [mailto:<a href="mailto:ipopt-bounces@coin-or.org" target="_blank">ipopt-bounces@coin-or.<wbr>org</a>]

<b>On Behalf Of </b>Damien<br>

<b>Sent:</b> Tuesday, 10 January 2017 4:11 p.m.<br>

<b>To:</b> <a href="mailto:ipopt@list.coin-or.org" target="_blank">ipopt@list.coin-or.org</a><br>

<b>Subject:</b> Re: [Ipopt] Any method to speed up the NLP solution via IPOPT<u></u><u></u></span></p>

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<p class="MsoNormal"><u></u> <u></u></p>

<p>Fan,<u></u><u></u></p>

<p>If you're using MKL Pardiso, one of the things we found that really helps speed on our optimal control problems is setting "pardiso_redo_symbolic_fact_<wbr>only_if_inertia_wrong" to "yes".  On large problems the symbolic factorisation can take a long time.

<u></u><u></u></p>

<p class="MsoNormal" style="margin-bottom:12.0pt">Damien<u></u><u></u></p>

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<p class="MsoNormal">On 1/9/2017 8:06 PM, zhadamfan wrote:<u></u><u></u></p>

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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif">To whom it may concern,

<u></u><u></u></span></p>

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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif"><u></u> <u></u></span></p>

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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif">I am trying to solve the nonlinear model predictive control problem. In each loop, a large-scale NLP is required to be sovled.<u></u><u></u></span></p>

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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif">To obtain a satisfying dynamic performance, a large predictive horizon is chosen. As a result, it takes a considerably long time to get the result.<u></u><u></u></span></p>

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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif"><u></u> <u></u></span></p>

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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif">Is there any method to speed up the compuation? For example, parallel computing or some other technique?<u></u><u></u></span></p>

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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif"><u></u> <u></u></span></p>

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<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif">I used the OPTI toolbox in Matlab 2016a on Windows 7, 64bit. I checked the instruction on OPTI wiki. It is said that </span><span style="font-size:10.0pt;font-family:"Verdana",sans-serif;color:#1b1b1b">PARDISO

 is helpful. However, the effectiveness is limited.</span><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif"><u></u><u></u></span></p>

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<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Verdana",sans-serif;color:#1b1b1b;background:white"><br>

<br>

</span><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif"><u></u><u></u></span></p>

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<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Verdana",sans-serif;color:#1b1b1b">Thank you for any helpful suggestions sincerely. Looking forward to your reply.</span><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif"><u></u><u></u></span></p>

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<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Verdana",sans-serif;color:#1b1b1b"><br>

<br>

</span><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif"><u></u><u></u></span></p>

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<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Verdana",sans-serif;color:#1b1b1b">Best regards</span><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif"><u></u><u></u></span></p>

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<p class="MsoNormal"><span style="font-size:10.0pt;font-family:"Verdana",sans-serif;color:#1b1b1b">Fan</span><span style="font-size:10.5pt;font-family:"Microsoft YaHei",sans-serif"><u></u><u></u></span></p>

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<p class="MsoNormal"><br>

<br>

<br>

<u></u><u></u></p>

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<pre>Ipopt mailing list<u></u><u></u></pre>

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<p class="MsoNormal"><u></u> <u></u></p>

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