Questions tagged [ipopt]

Ipopt (Interior Point OPTimizer, pronounced eye-pea-Opt) is a software package for large-scale ​nonlinear optimization. Ipopt is written in C++ and is released as open source code under the Eclipse Public License (EPL). It is available from the ​COIN-OR initiative.

Introduction

Ipopt (Interior Point OPTimizer, pronounced eye-pea-Opt) is a software package for large-scale nonlinear optimization. It is designed to find (local) solutions of mathematical optimization problems of the form

   min     f(x)
x in R^n

s.t.       g_L <= g(x) <= g_U
           x_L <=  x   <= x_U

where f(x): R^n --> R is the objective function, and g(x): R^n --> R^m are the constraint functions. The vectors g_L and g_U denote the lower and upper bounds on the constraints, and the vectors x_L and x_U are the bounds on the variables x. The functions f(x) and g(x) can be nonlinear and nonconvex, but should be twice continuously differentiable. Note that equality constraints can be formulated in the above formulation by setting the corresponding components of g_L and g_U to the same value.

Ipopt is part of the COIN-OR Initiative.

Background

Ipopt is written in C++ and is released as open source code under the Eclipse Public License (EPL). It is available from the COIN-OR initiative. The code has been written by Andreas Wächter and Carl Laird. The COIN-OR project managers for Ipopt are Andreas Wächter und Stefan Vigerske.

The C++ version has first been released on Aug 26, 2005 as version 3.0.0. The previously released pre-3.0 Fortran version is no longer maintained.

The Ipopt distribution can be used to generate a library that can be linked to one's own C++, C, Fortran, or Java code, as well as a solver executable for the AMPL modeling environment. The package includes interfaces to CUTEr optimization testing environment, as well as the MATLAB and R programming environments. IPOPT can be used on Linux/UNIX, Mac OS X and Windows platforms.

As open source software, the source code for Ipopt is provided without charge. You are free to use it, also for commercial purposes. You are also free to modify the source code (with the restriction that you need to make your changes public if you decide to distribute your version in any way, e.g. as an executable); for details see the EPL license. And we are certainly very keen on feedback from users, including contributions!

In order to compile Ipopt, certain third party code is required (such as some linear algebra routines). Those are available under different conditions/licenses.

Related Projects

COIN-OR/ADOL-C: Using Ipopt via C++ and automatic differentiation (examples).

COIN-OR/AIMMSlinks: Using Ipopt via AIMMS

COIN-OR/CppAD: Using Ipopt via C++ and automatic differentiation (example).

COIN-OR/GAMSlinks: Using Ipopt via GAMS

COIN-OR/Optimization Services: Using Ipopt via OS

APMonitor: MATLAB, Python, and Web Interface to Ipopt with APMonitor for Android, Linux, Mac, and Windows OS

CasADi: Using Ipopt in a symbolic framework for automatic differentiation and numeric optimization.

csipopt: Interfacing Ipopt from .NET languages such as C#, F# and Visual Basic.NET.

GEKKO: Python optimization suite with IPOPT: pip install gekko

JuMP: Algebraic modeling with automatic differentiation in Julia (low-level interface also available)

MADOPT: Light-weight C++ and Python modelling interfaces implementing expression building using operator overloading and automatic differentiation.

mexIPOPT: a rewrite of the MATLAB interface that is contained in Ipopt

OPTI Toolbox: Windows x86 + x64 MATLAB Interface, including binaries

pyipopt: Interfacing Ipopt from Python

sci-ipopt: Interfacing Ipopt from Scilab (a free MATLAB-like environment)

(this description is a stripped-down port of the official page)

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Initializing filter in IPOPT

I am currently developing an algorithm where I am manually updating the barrier parameter when some conditions of mine are true, and than calling IPOPT optimize. Like this, set_optimizer_attributes(model, "mu_target" => my_μ, "mu_init" => my_μ, …
Annaquest
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No executable found for solver 'ipopt' in Ubuntu

I am trying to solve an optimization problem in pyomo by using ipopt as solver. My OS is ubuntu. However I am getting the following error" pyomo.common.errors.ApplicationError: No executable found for solver 'ipopt' I tried the solution mentioned…
Kosmylo
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Can I get Ipopt's version from the C++ interface?

I can get Ipopt's version from an executable via the command line: ipopt --version. However, I would like to get the version from the c++ interface, which does not use the executable. Is this possible? For context, I have installed Ipopt following…
rbparker
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Pyomo cannot find ipopt in Linux even though it's installed

I'm using Kali Linux and I needed to install ipopt to use with pyomo in Python which I'm currently learning. I have tried several things and none of them have worked with trying to run ipopt in pyomo. First, following their official website's…
Shen
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Pyomo: Getting KeyError: 2472563968992

I just started to use pyomo. I am trying to solve a dynamic optimization problem with it. But I am getting KeyError: 2472563968992, which I could not understand. import numpy as np import matplotlib.pyplot as plt from pyomo.dae import ContinuousSet,…
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Bonmin fails with error code -9 from ASL (AMPL solver library), what does that code even mean?

I am trying to solve a linear problem using Bonmin, the sample size is 5000 records. Ipopt and Cbc solved the same problem and data without any issues. Whereas, Bonmin always fails with the below error: ERROR: Solver (asl) returned non-zero return…
rk1918
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IpoptSolver has not been compiled as part of this binary

I have freshly installed drake using pip and while going through tutorials about mathematical programs, I cannot use the example with IpoptSolver. I am getting this error message, however, I cannot find information in the documentation how to…
zenzu
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How to compile ipopt with BLIS and libFLAME on Windows with MinGW or/and cygwin

Related to my other question, I was trying to compile ipopt with the BLIS and libFLAME library, but am still struggling to get this set up correctly. Since there are many different sources of information, I will provide a full history of what I've…
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Cyipopt fails to converge for NLP problem which fmincon() can solve

I'm currently trying to implement a python script for solving a constrained nonlinear optimization problem with ~800 variables and 2 constraints, one linear and one nonlinear. There already exists a Matlab implementation of this script and I'm…
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Constraints of type MathOptInterface.VariableIndex-in-MathOptInterface.ZeroOne are not supported by the solver. When using Ipopt solver in Julia

Need help in resolving issue of Constraints of type MathOptInterface.VariableIndex-in-MathOptInterface.ZeroOne are not supported by the solver. When using Ipopt solver in Julia for BinPacking problem #variables declaration @variable(model,…
Dones
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Changing IPOPT options with pyomo doesn't work

I am using IPOPT solver for solving KKTs conditions (a bunch of equality constraints and complementarity conditions). For assigning the solver for the complementarity problem, I use the command line below: solver = po.SolverFactory('mpec_nlp') And…
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Nonlinear Optimization of absolute value function using ipopt solver

How to Solve Nonlinear Optimization Problem when Objective function is a Modulus (absolute) valued function using IPOPT Solver in python?
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pyomo/ipopt: nonlinear optimization problem not converging

The question (very short version) Why can I not decrease the lower boundary for the decision variable model.v_dot (see implementation) below 30 ? As soon as I do so, the solver doesn't return results. After only one iteration I get the solver…
Khalilbs
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How to convert a Python Script constains Pyomo, GLPK, IPOPT to single exe app with Pyinstaller

I am trying to build a program which solves linear programming problems. I decided to use pyomo as package and glpk and ipopt as optimizers. I need to convert my Python script to single exe file. I used Pyinstaller but there is…
firattamur
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How to get values from every iteration in JuMP

I'm solving a particular optimization problem in julia using JuMP, Ipopt and I have a problem finding the history of values i.e. value of x from every iteration. I couldn't find anything useful in documentations. Minimal example: using JuMP import…