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To whom it may concern,<div><br></div><div>I am trying to solve the nonlinear model predictive control problem. In each loop, a large-scale NLP is required to be sovled.</div><div>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.</div><div><br></div><div>Is there any method to speed up the compuation? For example, parallel computing or some other technique?</div><div><br></div><div>I used the OPTI toolbox in Matlab 2016a on Windows 7, 64bit. I checked the instruction on OPTI wiki. It is said that <span style="color: rgb(27, 27, 27); font-family: Verdana, Arial, Helvetica, sans-serif; font-size: 13.1424px; orphans: 2; widows: 2; background-color: rgb(255, 255, 255);">PARDISO is helpful. However, the effectiveness is limited.</span></div><div><span style="color: rgb(27, 27, 27); font-family: Verdana, Arial, Helvetica, sans-serif; font-size: 13.1424px; orphans: 2; widows: 2; background-color: rgb(255, 255, 255);"><br></span></div><div style="orphans: 2; widows: 2;"><font color="#1b1b1b" face="Verdana, Arial, Helvetica, sans-serif"><span style="font-size: 13.1424px; background-color: rgb(255, 255, 255);">Thank you for any helpful suggestions </span><span style="font-size: 13.1424px;">sincerely. Looking forward to your reply.</span></font></div><div style="orphans: 2; widows: 2;"><font color="#1b1b1b" face="Verdana, Arial, Helvetica, sans-serif"><span style="font-size: 13.1424px; background-color: rgb(255, 255, 255);"><br></span></font></div><div style="orphans: 2; widows: 2;"><font color="#1b1b1b" face="Verdana, Arial, Helvetica, sans-serif"><span style="font-size: 13.1424px; background-color: rgb(255, 255, 255);">Best regards</span></font></div><div style="orphans: 2; widows: 2;"><font color="#1b1b1b" face="Verdana, Arial, Helvetica, sans-serif"><span style="font-size: 13.1424px; background-color: rgb(255, 255, 255);">Fan</span></font></div></div></body>