Open Source Algorithms
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Browse free open source Algorithms and projects below. Use the toggles on the left to filter open source Algorithms by OS, license, language, programming language, and project status.
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lpsolve
Mixed Integer Linear Programming (MILP) solver.
Mixed Integer Linear Programming (MILP) solver lp_solve solves pure linear, (mixed) integer/binary, semi-cont and special ordered sets (SOS) models.lp_solve is written in ANSI C and can be compiled on many different platforms like Linux and WINDOWS This project is moved to github: https://lp-solve.github.io/ -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads: http://arma.sourceforge.net/download.html * Documentation: http://arma.sourceforge.net/docs.html * Bug reports: http://arma.sourceforge.net/faq.html * Git repo: https://gitlab.com/conradsnicta/armadillo-code -
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CRC RevEng
Arbitrary-precision CRC calculator and algorithm finder
CRC RevEng is a portable, arbitrary-precision CRC calculator and algorithm finder. It calculates CRCs using any of the 113 preset algorithms, or a user-specified algorithm to any width. It calculates reversed CRCs to give the bit pattern that produces a desired forward CRC. CRC RevEng also reverse-engineers any CRC algorithm from sufficient correctly formatted message-CRC pairs and optional known parameters. It comprises powerful input interpretation options. Compliant with Ross Williams' Rocksoft(tm) model of parametrised CRC algorithms. -
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The JTS Topology Suite is an API for modelling and manipulating 2-dimensional linear geometry. It provides numerous geometric predicates and functions. JTS conforms to the Simple Features Specification for SQL published by the Open GIS Consortium.
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Linear Program Solver
Solve linear programming problems
Linear Program Solver (LiPS) is an optimization package oriented on solving linear, integer and goal programming problems. The main features of LiPS are: ● LiPS is based on the efficient implementation of the modified simplex method that solves large scale problems. ● LiPS provides not just an answer, but a detailed solution process as a sequence of simplex tables, so you can use it for studying/teaching linear programming. ● LiPS gives sensitivity analysis procedures, which allow us to study the behaviour of the model when you change its parameters, including: analysis of changes in the right sides of constraints, analysis of changes in the coefficients of the objective function, analysis of changes in the column/row of the technology matrix. Such information may be extremely useful for the practical application of LP Models. ● LiPS provides methods of goal programming, including lexicographic and weighted GP methods, which are oriented on multi-objective optimisation. -
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Linear Program Solver (Solvexo) is an optimization package intended for solving linear programming problems. The main features of the Solvexo are: · Solvexo solver is based on the efficient implementation of the simplex method (one or two phases); · Solvexo provides not only an answer, but a detailed solution process as a sequence of simplex matrices, so you can use it in studying (teaching) linear programming. · Solvexo provides a solution with the graphic method for problems with tow variables. · This updated version includes two languages English and French. If you have any questions, feel free to contact me: romdhani.mohamed.ali@gmail.com. Any comments and suggestions would be helpful!
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ViennaCL
Linear algebra and solver library using CUDA, OpenCL, and OpenMP
ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects. -
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Continuation Core and Toolboxes (COCO)
Toolboxes for parameter continuation and bifurcation analysis.
Development platform and toolboxes for parameter continuation, e.g., bifurcation analysis of dynamical systems and constrained design optimization. This material is based upon work partially supported by the National Science Foundation under Grant No. 1016467 and the Danish research council (FTP) under the project number 0602-00753B. Any opinions, findings, and conclusions or recommendations expressed on this site are those of the authors and do not necessarily reflect the views of the National Science Foundation or other funding sources. Documentation and tutorials are available for the following toolboxes: * ep : continuation and bifurcations of equilibrium points * coll : continuation of constrained collections of trajectory segments, including multi-segment boundary-value problems * po : continuation and bifurcations of periodic orbits in smooth and hybrid systems * recipes : collection of examples from the book Recipes for Continuation -
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The Modular toolkit for Data Processing (MDP) is a Python data processing framework. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded. The implementation of new algorithms is easy and intuitive. The new implemented units are then automatically integrated with the rest of the library. The base of available algorithms is steadily increasing and includes signal processing methods (Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several classifiers, probabilistic methods (Factor Analysis, RBM), data pre-processing methods, and many others.
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That project (RMOL) aims at giving developers concerned by the Revenue Management arena a library delivering a reference implementation for most of the published algorithms and methods. That library is intended to be used in simulated environment: it does not intend to be used in real world production systems.
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Bandicoot
fast C++ library for GPU linear algebra & scientific computing
* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code -
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Math Tools
Provides useful mathematical tools which make your work much easier.
Math Tools provides mathematical tools, allows you to calculate triangle propeties, and find both parametric and algebraic forms of planes. ------ More Tools Will be Added in The Future ------ ------ Translation to english will be completed soon ------ -
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HungarianAlgorithm
An Ada implementation of the Hungarian Algorithm to minimize cost
The Hungarian algorithm can be described as optimally solving a workers versus jobs assignment problem that minimizes total cost. This implementation assumes a square cost matrix, i.e. the number of jobs equals the number of workers to do them. -
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Digraph3
A collection of python3 modules for Algorithmic Decision Theory
This collection of Python3 modules provides a large range of implemented decision aiding algorithms useful in the field of outranking digraphs based Multiple Criteria Decision Aid (MCDA), especially best choice, linear ranking and absolute or relative rating algorithms with multiple incommensurable criteria. Technical documentation and tutorials are available under the following link: https://digraph3.readthedocs.io/en/latest/ The tutorials introduce the main objects like digraphs, outranking digraphs and performance tableaux. There is also a tutorial provided on undirected graphs. Some tutorials are problem oriented and show how to compute the winner of an election, how to build a best choice recommendation, or how to linearly rank or rate with multiple incommensurable performance criteria. Other tutorials concern more specifically operational aspects of computing maximal independent sets (MISs) and kernels in graphs and digraphs. -
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Foreval
Foreval is parser & compiler of mathematical expressions
Foreval is compiler of mathematical expressions (formulas) (directly to x86-32 CPU/FPU comand) given as string at run-time. Present as "dll" library and Delphi sources. Can be compiled in FPC (Lazarus). Can be direct connection to the program (without dll). Сurrent version ( v. 9.1.1.393): Examples for Delphi, Lazarus , GCC (Codeblock), (Builder, MSVC - in b.366). Demo: Fractals Julia; Visualizing of functions of complex variable - complex domain coloring , graph plotting & finding roots F(x), Fourier series. Old version (v.8.4.17.250): Examples for Delphi, FPC, Builder, MSVC , GCC (Codeblock) , VB6, FreeBasic. Download files: Foreval_all.7z (Foreval v9 + Foreval v8 + ForevalZ + all examples + doc) - recommend ForevalG9.7z (Foreval v9 + examples v9+ doc) (math parser, math expression parser, evaluate formula, evaluator, symbolic, differentiation, derivative , complex) -
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A library including the whole bunch of standard algorithms in graph optimization and drawing. On top of this, a GUI for manipulating and editing of graphs.
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TSP Solver and Generator
Generate and solve Travelling Salesman Problem tasks
TSPSG is intended to generate and solve Travelling Salesman Problem (TSP) tasks. It uses Branch and Bound method for solving. An input is a number of cities and a matrix of city-to-city travel prices. The matrix can be populated with random values in a given range (useful for generating tasks). The result is an optimal route, its price, step-by-step matrices of solving and solving graph. The task can be saved in internal binary format and opened later. The result can be printed or saved as PDF, HTML, or ODF. TSPSG may be useful for teachers to generate test tasks or just for regular users to solve TSPs. Also, it may be used as an example of using Branch and Bound method to solve a particular task. -
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The C++-programs simulate : Nondeterministic/Deterministic Multitape Turing & Post Machines, Universal Turing Machine, Turing Machine with faults, failures and recovery.
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Programmer's library for random numbers. Also random number generator testing code. Intended for simulation, games and "Monte-Carlo" algorithms.
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A Java library and set of tools to quickly and easily manipulate graphs (set of nodes and edges) and dynamic graphs. The principal trait of this library is its ability to manage (create, edit, layout, display) continuously evolving graphs. The development of this project now takes place on Github. Visit the official Graphstream website at http://graphstream-project.org
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C++ BigInt class
C++ BigInt class enables to work with arbitrary precision integers
C++ BigInt class that enables the user to work with arbitrary precision integers. Latest Version: 10.3 (2019-03-06) -
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OpenDiscreteDynamicProgrammingTemplate : founds optimal constrainted parameters of a discrete controls with second order optimization template replacing Hessian with directional derivatives and backpropagation for digital filter(as neural network)
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Opt4J
Modular Java framework for meta-heuristic optimization
Opt4J is an open source Java-based framework for evolutionary computation. It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary meta-heuristic optimization algorithms. For this purpose, Opt4J relies on a module-based implementation and offers a graphical user interface for the configuration as well as a visualization of the optimization process. -
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