Search Results for "nonlinear optimization"
Sort By:
Showing 26 open source projects for "nonlinear optimization"
View related business solutions-
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
-
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
-
1
The NLopt module for Julia
Package to call the NLopt nonlinear-optimization library from Julia
This module provides a Julia-language interface to the free/open-source NLopt library for nonlinear optimization. NLopt provides a common interface for many different optimization algorithms. -
2
Theseus
A library for differentiable nonlinear optimization
Theseus is a library for differentiable nonlinear optimization that lets you embed solvers like Gauss-Newton or Levenberg–Marquardt inside PyTorch models. Problems are expressed as factor graphs with variables on manifolds (e.g., SE(3), SO(3)), so classical robotics and vision tasks—bundle adjustment, pose graph optimization, hand–eye calibration—can be written succinctly and solved efficiently. -
3
JuMP
Modeling language for Mathematical Optimization
JuMP is a modeling language and collection of supporting packages for mathematical optimization in Julia. JuMP makes it easy to formulate and solve a range of problem classes, including linear programs, integer programs, conic programs, semidefinite programs, and constrained nonlinear programs. JuMP is used to solve large-scale inventory routing problems at Renault, schedule trains at Thales Inc., plan power grid expansion at PSR, and route school buses. -
4
EAGO.jl
A development environment for robust and global optimization
EAGO is an open-source development environment for robust and global optimization in Julia. EAGO is a deterministic global optimizer designed to address a wide variety of optimization problems, emphasizing nonlinear programs (NLPs), by propagating McCormick relaxations along the factorable structure of each expression in the NLP. Most operators supported by modern automatic differentiation (AD) packages (e.g., +, sin, cosh) are supported by EAGO and a number of utilities for sanitizing native Julia code and generating relaxations on a wide variety of user-defined functions have been included. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
CasADi
CasADi is a symbolic framework for numeric optimization
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 in C++, Python, or Matlab/Octave. CasADi's backbone is a symbolic framework implementing forward and reverse modes of AD on expression graphs to construct gradients, large-and-sparse Jacobians, and... -
6
Convex.jl
A Julia package for disciplined convex programming
Convex.jl is a Julia package for Disciplined Convex Programming (DCP). Convex.jl makes it easy to describe optimization problems in a natural, mathematical syntax, and to solve those problems using a variety of different (commercial and open-source) solvers. Convex.jl works by transforming the problem—which possibly has nonsmooth, nonlinear constructions like the nuclear norm, the log determinant, and so forth—into a linear optimization problem subject to conic constraints. ... -
7
Adaptive Simulated Annealing (ASA)
simulated annealing optimization and importance-sampling
Adaptive Simulated Annealing (ASA) is a C-language code that finds the best global fit of a nonlinear cost-function over a D-dimensional space. ASA has over 100 OPTIONS to provide robust tuning over many classes of nonlinear stochastic systems. -
8
LMath library
Math library for Free Pascal and Lazarus.
...It is entirely written in Pascal and does not depend on external libraries. LMath provides routines and demo programs for numerical analysis, including mathematical functions, probabilities, matrices, optimization, linear and nonlinear equations, integration, Fast Fourier Transform, random numbers, curve fitting, statistics and graphics. It is organized s set of lazarus packages which makes it easily extensible and helps to include only really needed features in your project. -
9
GRAMPC
A gradient-based augmented Lagrangian framework for embedded NMPC
GRAMPC is a nonlinear MPC framework that is suitable for dynamical systems with sampling times in the (sub)millisecond range and that allows for an efficient implementation on embedded hardware. The algorithm is based on an augmented Lagrangian formulation with a tailored gradient method for the inner minimization problem. GRAMPC is implemented in plain C with an additional interface to C++ and MATLAB/Simulink. -
Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
10
PRIMA
PRIMA is a package for solving general nonlinear optimization problems
PRIMA is a package for solving general nonlinear optimization problems without using derivatives. It provides the reference implementation for Powell's derivative-free optimization methods, i.e., COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. PRIMA means Reference Implementation for Powell's methods with Modernization and Amelioration, P for Powell. PRIMA is a package for solving general nonlinear optimization problems without using derivatives. ... -
11
ME.com
Mathematical & engineering components for software development
The truth can't be complicated. Mathematical & engineering components (abbreviation ME . com) for development of the software are the comprehensive collection of original fastest algorithms for scientific computing. Not based on any known software library. Used in AtteStat, StatAnt, Criterial projects and another with rights saved include in educational purposes. Registered 2003-03-21 with the Federal Service for Intellectual Property. Completely free. No donation required. Mathematical &... -
12
Algorithms Math Models
MATLAB implementations of algorithms
Algorithms_MathModels is a large MATLAB collection of algorithms and solved examples targeted at students and teams preparing for mathematical modeling competitions (national and international contests like MCM/ICM). The repository gathers implementations and case studies across many topics commonly used in contest solutions: optimization (linear, integer, goal and nonlinear programming), heuristic and metaheuristic methods (simulated annealing, genetic algorithms, immune algorithms), neural networks and time-series methods, interpolation and regression, graph theory, cellular automata, grey systems, fuzzy models, partial/ordinary differential equations, and multivariate analysis, among others. ... -
13
OptimTraj
A trajectory optimization library for Matlab
OptimTraj is a MATLAB toolbox for solving trajectory optimization problems. It supports direct collocation, shooting methods, and pseudospectral methods for finding optimal control inputs and system trajectories. It is useful for robotics, aerospace, biomechanics, and any domain requiring time-optimal or energy-optimal motion planning. -
14
NLOptControl.jl
nonlinear control optimization tool
This software solves nonlinear control problems at a high level very quickly. -
15
NOMAD is a C++ code that implements the MADS algorithm (Mesh Adaptive Direct Search) for difficult blackbox optimization problems. Such problems occur when the functions to optimize are costly computer simulations with no derivatives.
-
16
Crevice
Modeling environment for linear and nonlinear optimization
Crevice provides a modeling environment for linear and nonlinear optimization and bindings for solver libraries. Binaries for 32 and 64bit Windows as well as makefiles for Linux are available. -
17
GADfit
Global nonlinear optimization with automatic differentiation
NOTE: Development continued at GitHub! Current version is higher than 1.2.0. GADfit is a Fortran implementation of global nonlinear curve fitting, based on a modified Levenberg-Marquardt algorithm. Global fitting refers to fitting many datasets simultaneously with some parameters shared among the datasets. The fitting procedure is very fast and accurate thanks to the use of automatic differentiation. The model curves (fitting functions) can be of essentially arbitrary complexity. This... -
18
OptimC
OptimC - Optimization / Unconstrained Minimization Library in ANSI C
OptimC is a C software package to minimize any unconstrained multivariable function. The algorithms implemented are Nelder-Mead,Newton Methods (Line Search and Trust Region methods), Conjugate Gradient and BFGS (regular and Limited Memory). Brent method is also available for single variable functions if the bounds are known. Update 06/09/2014 - Nonlinear Squares Implementation [Levenberg-Marquardt Method] Added. Documentation - http://code.google.com/p/optimc/ -
19
JBernstein
JBernstein: Exploration techniques for non-linear constraint checking
JBernstein is a tool implemented in Java that enables to check whether a polynomial constraint holds for all variables within their domain. It is mainly used in the verification or synthesis of cyber-physical systems where the system model is nonlinear. The tool also supports specifications in assume-guarantee style. The underlying algorithm is based on a translation to Bernstein polynomials, and several optimization techniques are implemented to ensure efficiency. Concerning performance, the tool enables to check all examples in the PVS Bernstein testsuite within a second, which can be an order of magnitude faster than some other tools such as QEPCAD or REDLOG. ... -
20
Spreadsheet Template for Structural Engineering (FEA Analysis for beams, trusses, 2D-frames). It makes possible to create your own parametric models.Templates for engineering calculation (fatigue, concrete plates, etc)
-
21
Large Scale Optimization Templates
C++ templates with generic nonlinear optimization algorithms
Highly tunable, simple to use collection of the templates, containing a set of classes for solving unconstrained large scale nonlinear optimization problems. Currently it contains: -- Limited Memory Quasi Newton (L-BFSG) -- BFSG -- Conjugate Gradient -- Gradient Descent -- Wolf condition Line Search -- Backtracking Line Search -- Exact Golden Search -- Golden Search with Wolf condition We also distribute a set of tests with the library. -
22
ACADO Toolkit
Toolkit for Automatic Control and Dynamic Optimization
ACADO Toolkit is a software environment and algorithm collection for automatic control and dynamic optimization. It provides a general framework for using a great variety of algorithms for direct optimal control, including model predictive control, state and parameter estimation and robust optimization. ACADO Toolkit is implemented as self-contained C++ code and comes along with user-friendly MATLAB interface. The object-oriented design allows for convenient coupling of existing optimization... -
23
...MTL was used to build a 3d Scanner. MTL consists of pars B - Basic Functions, Matrices, Images, Hypermodels (3d Models and up) N - Numeric Functions ranging from linear regression over nonlinear optimization to singular-value computation I - Image filters and Image enhancement H - Hardware related (optional part), does require additional libraries and is only useful on certain hosts. G - Hyper-Model functions such as ray-plane intersections etc.
-
24
OptLib
C nonlinear optimization library
[PROJECT MIGRATED TO GIT-HUB] OptLib is a library of nonlinear optimization routines focused on the use of stochastic methods, including Simulated Annealing, Genetic Algorithms, and Monte Carlo. Routines are parallelized using MPI. -
25
A Python environment for large and sparse linear and nonlinear optimization using intuitive interfaces to linear algebra tools and subproblem solvers written in low-level languages. It provides building blocks to experiment with new ideas and algorithms.
