Quadratic programming solvers in Python with a unified API
The main features of qpsolvers/qpsolvers are: Optimization Solvers.
Open-source alternatives to qpsolvers/qpsolvers include: ceres-solver/ceres-solver — Ceres Solver is a C++ library for numerical optimization, specializing in non-linear least squares and unconstrained… cma-es/libcmaes — libcmaes is a multithreaded C++11 library with Python bindings for high performance blackbox stochastic optimization… coin-or/ipopt — COIN-OR Interior Point Optimizer IPOPT. coin-or/shot — A solver for mixed-integer nonlinear optimization problems. cvxgrp/scs — Splitting Conic Solver. casadi/casadi — CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse…
Ceres Solver is a C++ library for numerical optimization, specializing in non-linear least squares and unconstrained optimization problems. It serves as a framework for automatic differentiation and robust curve fitting, providing tools to solve large-scale mathematical models. The library is distinguished by its bundle adjustment capabilities, which exploit sparse matrix structures to refine 3D scene points and camera parameters. It utilizes dual-number automatic differentiation to compute derivatives of cost functions, removing the need for manual Jacobian derivation. The project covers a
libcmaes is a multithreaded C++11 library with Python bindings for high performance blackbox stochastic optimization using the CMA-ES algorithm for Covariance Matrix Adaptation Evolution Strategy
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.
