Search Results for "nonlinear optimization"
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Showing 12 open source projects for "nonlinear optimization"
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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. -
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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. -
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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 &... -
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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. ... -
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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.
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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... -
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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. ... -
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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. -
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...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.
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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. -
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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.
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H2O is a collection of C routines and applications designed for the optimization of multi-reservoir and multi-period hydrothermal power production scheduling. H2O is built upon nonlinear network algorithms and heuristic techniques for higher efficiency.
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