ipoptjlr

Optimization tool

A software package providing an interface to the Ipopt nonlinear solver in R, enabling optimization and solving complex mathematical problems.

GitHub

6 stars
2 watching
1 forks
Language: R
last commit: almost 6 years ago
ipoptoptimizationr

Related projects:

Repository Description Stars
non-contradiction/convexjlr An R package for using the Julia Convex.jl package for Disciplined Convex Programming (DCP) optimization. 14
grid-parity-exchange/egret A Python-based package for solving optimization problems in power systems 133
stevengj/nlopt A unified interface and packaging of several nonlinear optimization libraries for global and local optimization. 1,892
non-contradiction/autodiffr Automates differentiation of R functions using Julia 23
rflamary/nonconvex-optimization A Matlab toolbox providing a generic solver for proximal gradient descent in convex and non-convex optimization problems with various regularization terms. 49
ethz-adrl/ifopt An Eigen-based C++ interface to nonlinear programming solvers 787
nicolasboumal/manopt A Matlab toolbox for optimizing functions on geometric spaces defined by constraints or regularization terms 314
metaopt/torchopt An efficient library for differentiable optimization built on top of PyTorch. 544
project-pareto/project-pareto An optimization framework for managing produced water and its beneficial reuse 18
vindaar/nimnlopt A wrapper around the Nlopt nonlinear optimization library for Nim programming language 16
yelp/moe An optimization tool for finding parameters in complex systems with expensive or time-consuming evaluation processes. 1,308
cvxopt/cvxopt A Python software suite for solving convex optimization problems 988
jnagy1/irtools A collection of iterative regularization methods and large-scale test problems for linear inverse problems. 88
jiangoforit/yellowfin_pytorch An optimizer that automatically tunes momentum and learning rate using local quadratic approximation. 287
locuslab/optnet A PyTorch module that adds differentiable optimization as a layer to neural networks 513