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mexIPOPT

by Enrico Bertolazzi

This is my rewrite of Peter Carbonetto MATLAB interface for IPOPT a software package for large-scale ​nonlinear optimization.

Source code and documentation for IPOPT can be downloaded from:

https://projects.coin-or.org/Ipopt

On OSX IPOPT can be installed using Homebrew (http://brew.sh).

Why do a job already done?

The original MATLAB interface (https://projects.coin-or.org/Ipopt/wiki/MatlabInterface) seems not maintained for OSX and do not work with recent MATLAB distributions. I have reorganized and simplified the original interface (only internally) and eliminated the bug (due to MATLAB change in the managing of sparse pattern) in the interfacing of sparse pattern between MATLAB and IPOPT. Moreover I tried to improve error catching.

How to install

Use the toobox installer at

• https://github.com/ebertolazzi/mexIPOPT/releases

download and run in MATLAB to install following the instruction.

How to compile

Compilation shuold be not necessary. To (re-)compile the mex file for your architecture

• change the working directory to the toolbox directory.
• run the script CompileIpoptMexLib.

if all the thing go well open

• run the script setup and them ../IPOPT-toolbox.prj to compile the toolbox.

at this point you find the recompiled toolbox at

• ../IPOPT-toolbox.mltbx

Examples

In the directory toolbox/example you find the original examples of Peter Carbonetto which shows the usage of the interface.

In the directory test_TRAIN you find a complex example of an Optimal Control Problem solved using direct trascription and transformed to an NLP solved using IPOPT. The descriptin of the problem is at

• https://vanderbei.princeton.edu/tex/trajopt/trajopt.pdf.

MA57, MA77, MA86, MA97, PARDISO

IPOPT can can use HSL library (https://www.hsl.rl.ac.uk) and PARDISO (https://pardiso-project.org). These libraries can improve the performance of the solver. Due to copyright issues these libraries cannot be included in IPOPT executable. Read README_HSL.md to see how to use these libraries in your applications.

Author:

Enrico Bertolazzi
Department of Industrial Engineering
University of Trento
[email protected]