Additionally, the IPOPT distribution includes interfaces for
There is also software that facilitates use of IPOPT maintained by other people, among them are:
ADOL-C facilitates the evaluation of first and higher derivatives of vector functions that are defined by computer programs written in C or C++. It comes with examples that show how to use it in connection with IPOPT, see https://projects.coin-or.org/ADOL-C.
The AIMMSlinks project on COIN-OR, maintained by Marcel Hunting, provides an interface for IPOPT within the AIMMS modeling tool, see https://projects.coin-or.org/AIMMSlinks.
MATLAB, Python, and Web Interface to Ipopt for Android, Linux, MacOS X, and Windows, see http://apmonitor.com.
CasADi is a symbolic framework for automatic differentiation and numeric optimization and comes with IPOPT, see http://casadi.org.
Given a C++ algorithm that computes function values, CppAD generates an algorithm that computes corresponding derivative values (of arbitrary order using either forward or reverse mode). It comes with an example that shows how to use it in connection with IPOPT, see https://projects.coin-or.org/CppAD.
The GAMSlinks project on COIN-OR includes a GAMS interface for IPOPT, see https://projects.coin-or.org/GAMSlinks.
Julia is a high-level, high-performance dynamic programming language for technical computing. JuliaOpt, see http://juliaopt.org, is an umbrella group for Julia-based optimization- related projects. It includes the algebraic modeling language JuMP (https://github.com/JuliaOpt/JuMP.jl) and an interface to IPOPT (https://github.com/JuliaOpt/Ipopt.jl).
A rewrite of the above mentioned MATLAB Interface: https://github.com/ebertolazzi/mexIPOPT
Light-weight C++ and Python modelling interfaces implementing expression building using operator overloading and automatic differentiation, see https://github.com/stanle/madopt
An interface to the C# language is available here: https://github.com/cureos/csipopt
OPTI is a free Matlab toolbox for constructing and solving linear, nonlinear, continuous and discrete optimization problem and comes with IPOPT.
The Optimization Services (OS) project provides a set of standards for representing optimization instances, results, solver options, and communication between clients and solvers, incl. IPOPT, in a distributed environment using Web Services, see https://projects.coin-or.org/OS.
An interface to the python language is available here: https://github.com/xuy/pyipopt
A Scilab interface is available here: http://forge.scilab.org/index.php/p/sci-ipopt