Search Results for "genetic algorithms"
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Showing 206 open source projects for "genetic algorithms"
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PyGAD
Source code of PyGAD, Python 3 library for building genetic algorithms
PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine learning algorithms. It supports Keras and PyTorch. PyGAD supports optimizing both single-objective and multi-objective problems. PyGAD supports different types of crossover, mutation, and parent selection. PyGAD allows different types of problems to be optimized using the genetic algorithm by customizing the fitness function. -
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Nevergrad
A Python toolbox for performing gradient-free optimization
Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget) and then experiment with multiple strategies—evolutionary algorithms, Bayesian optimization, bandit methods, genetic algorithms, etc. ... -
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PlatEMO
Evolutionary multi-objective optimization platform
...PlatEMO consists of a number of MATLAB functions without using any other libraries. Any machines able to run MATLAB can use PlatEMO regardless of the operating system. PlatEMO includes more than ninety existing popular MOEAs, including genetic algorithm, differential evolution, particle swarm optimization, memetic algorithm, estimation of distribution algorithm, and surrogate model-based algorithm. Most of them are representative algorithms published in top journals after 2010. Users can select various figures to be displayed, including the Pareto front of the result, the Pareto set of the result, the true Pareto front, and the evolutionary trajectories of any performance indicator values. ... -
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Smile
Statistical machine intelligence and learning engine
Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM... -
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pgapack, the parallel genetic algorithm library is a powerfull genetic algorithm library by D. Levine, Mathematics and Computer Science Division Argonne National Laboratory. The library is written in C. PGAPy wraps this library for use with Python.
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Evolutionary Computation Framework
C++ framework for application of any type of evolutionary computation.
ECF is a framework intended for application of any type of evolutionary computation (GA/GP, DE, Clonalg, ES, PSO, ABC, GAn, local search...). It offers simplicity for the end-user (parameterless usage, tutorial) and customization for experienced EC practicioners. -
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Java·Applied·Geodesy·3D
Least-Squares Adjustment Software for Geodetic Sciences
JAG3D is no longer developed at source-forge, and has moved to GitHub. Please visit https://github.com/applied-geodesy/jag3d or https://software.applied-geodesy.org to get the latest version. -
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This is the official repository for the CUSTOMHyS-Qt software. CUSTOMHyS-Qt is a GUI for the CUSTOMHyS framework, which is an interactive tool for customysing heuristic-based algorithms. The CUSTOMHyS-Qt is written in Python and uses the PyQt5 library for the GUI. Further references about the backend can be found in the CUSTOMHyS repository.
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Evolutionary Algorithm
Evolutionary Algorithm using Python
Evolutionary Algorithm is an educational Python project that demonstrates evolutionary computation techniques such as genetic algorithms, evolution strategies, and neuroevolution in a clear and accessible way. Rather than being a single monolithic library, this repository provides a series of self-contained examples showing how different population-based search methods solve optimization problems and adapt candidate solutions over generations. Users can explore basic genetic algorithm setups, match phrase examples, pathfinding challenges, and microbial GA variants, as well as evolution strategy approaches like NES. ... -
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GeneticSharp
GeneticSharp is a fast, extensible, multi-platform and multithreading
GeneticSharp is a fast, extensible, multi-platform and multithreading C# Genetic Algorithm library that simplifies the development of applications using Genetic Algorithms (GAs). Can be used in any kind of .NET 6, .NET Standard and .NET Framework apps, like ASP .NET MVC, ASP .NET Core, Blazor, Web Forms, UWP, Windows Forms, GTK#, Xamarin, MAUI and Unity3D games. GeneticSharp and extensions (TSP, AutoConfig, Bitmap equality, Equality equation, Equation solver, Function builder, etc). ... -
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Sudoku Maker is a generator for Sudoku number puzzles. It uses a genetic algorithm internally, so it can serve as an introduction to genetic algorithms. The generated Sudokus are usually very hard to solve -- good for getting rid of a Sudoku addiction.
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Evolutionary.jl
Evolutionary & genetic algorithms for Julia
A Julia package for evolutionary & genetic algorithms. The package can be installed with the Julia package manager. -
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Triangula
Generate high-quality triangulated and polygonal art from images
...For almost all cases, only changing the number of points and leaving all other options with their default values will generate an optimal result. While all these algorithms are iterative algorithms, the main difference is that in the other algorithms triangles can overlap while Triangula generates a triangulation. -
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BioNetExplorer
Framework for Exploration of Bio-signal Processing DNNs in Wearables
...Our framework varies key neural architecture parameters to search for an embedded DNN with low hardware overhead that can be deployed in wearable edge devices to analyze the bio-signal data and to extract the relevant information, such as arrhythmia and seizure. Furthermore, BioNetExplorer reduces the exploration time by deploying genetic algorithms, such as NSGA-II, SPEA-2, etc. Our framework also enables hardware-aware DNN architecture search by imposing user requirements and hardware constraints (storage, FLOPs, etc.) during the exploration stage, thereby limiting the number of networks explored. In case of usage, please refer to: B. S. Prabakaran, A. Akhtar, S. ... -
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Smart Algorithm
Repository implementing a variety of intelligent algorithms
Smart-Algorithm is a repository implementing a variety of intelligent / metaheuristic optimization algorithms (e.g. Genetic Algorithm, Ant Colony, Particle Swarm, Immune Algorithm). The implementations are provided in multiple languages (Java, Python, MATLAB). The repository’s aim is to offer reference implementations of “smart” algorithms for tasks like route planning, optimization, or algorithm learning. Particle Swarm Optimization (PSO) implementations in multiple languages. ... -
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RGP Eugenics
Eugenics assumptions in genetic programing
Development of solutions in an automatic way using genetic programming and evolutionary algorithms is powerful. Assuming random starting point and following evolution principles we are capable to solve very complex problems. Question is what if we know some sub-optimal solutions and the evolution process will get so-called good start? The general purpose of the project is to get purely empirical answers for such question. -
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Skalli
IVS & ILRS Reference Point Determination
Skalli is a simple tool to estimate the IVS (International VLBI Service for Geodesy and Astrometry) and ILRS (International Laser Ranging Service) reference point of a radio or laser telescope. -
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SVPhylA
SVPhylA: Sequence Vectorization for Phylogenetic Analyses
...Such alignment-free methods basically encode DNA and protein sequences (fasta files) into numerical vectors allowing the calculation of alignment-free distances which may be combined into a consensus/compromise matrix by using algorithms like DISTATIS based on Multidimensional Scaling (MSD), Lineal Principal Component Analysis (PCA) and PCA-Kernel (non-lineal). In addition, genetic distances derived can be either combined between them or with the alignment-free distances. So far, SVPhylA contain a module to compare tree topologies by using different distance measures as a validation procedure. ... -
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OpenDino
Open Source Java platform for Optimization, DoE, and Learning.
OpenDino is an open source Java platform for optimization, design of experiment and learning. It provides a graphical user interface (GUI) and a platform which simplifies integration of new algorithms as "Modules". Implemented Modules Evolutionary Algorithms: - CMA-ES - (1+1)-ES - Differential Evolution Deterministic optimization algorithm: - SIMPLEX Learning: - a simple Artificial Neural Net Optimization problems: - test functions - interface for executing... -
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Xoptfoil
Airfoil optimization with Xfoil
Airfoil optimization using the highly-regarded Xfoil engine for aerodynamic calculations. Starting with a seed airfoil, Xoptfoil uses particle swarm, genetic algorithm and direct search methodologies to perturb the geometry and maximize performance. The user selects a number of operating points over which to optimize, desired constraints, and the optimizer does the rest. -
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sijinn
SImple Java Implementation of Neural Network
Alfa version - work in progress. Perseptron network structure. Can be saved in xml format. Training strategies: - Gradient Descent (Batch, Stochastic) - Genetic Breeding Training algorithms: - BPROP (back propagation) - QPROP (quick propagation) - RPROP (resilient propagation) - GENE (genetic neural) Demo: https://sijinn.herokuapp.com/ http://sijinn.appspot.com/network GitHub: https://github.com/surban1974/sijinn Maven <repositories> <repository> <id>neohort-mvn-repo</id> <url>https://github.com/surban1974/sijinn/raw/mvn-repo/</url> <snapshots> <enabled>true</enabled> <updatePolicy>always</updatePolicy> </snapshots> </repository> </repositories> <dependency> <groupId>com.github.surban1974.sijinn</groupId> <artifactId>sijinn-base</artifactId> <version>1.1.2-alfa</version> </dependency> -
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TEESer
Tool for Engineering Emergent Selforganizing bEhavioR
...Designers can continue to use their domain tools such as favorable simulator and by pluging it into the framework can take advantage of distributed simulations in the grid, various analyzers, optimizers (particle swarm optimization, genetic algorithms, ...). See Wiki pages for more information. -
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The source code has been migrated and is now hosted on Github: https://github.com/jenetics/jenetics Jenetics is an advanced Genetic Algorithm, Evolutionary Algorithm and Genetic Programming library, respectively, written in modern day Java. It is designed with a clear separation of the several algorithm concepts, e. g. Gene, Chromosome, Genotype, Phenotype, Population and fitness Function. Jenetics allows you to minimize or maximize the given fitness function without tweaking it. In...
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miRBond
miRBond: Genome-scale identification of miRNA-mRNA and miRNA-lncRNA in
Domestic animals show considerable genetic diversity. Previous studies suggested that animal phenotypes were affected by miRNA-mRNA interplay, but these studies focused mainly on the analysis of one or several miRNA-mRNA interactions. Whereas in this study, we present miRNA-mRNA and miRNA-lncRNA interactions on genome scale by using the miRanda and TargetScan algorithms. -
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popt4jlib
Parallel Optimization Library for Java
popt4jlib is an open-source parallel optimization library for the Java programming language supporting both shared memory and distributed message passing models. Implements a number of meta-heuristic algorithms for Non-Linear Programming, including Genetic Algorithms, Differential Evolution, Evolutionary Algorithms, Simulated Annealing, Particle Swarm Optimization, Firefly Algorithm, Monte-Carlo Search, Local Search algorithms, Gradient-Descent-based algorithms, as well as some well-known network flow and other graph algorithms. A fast parallel implementation of the network simplex method, and some full-fledged parallel/distributed MIP solvers will be added in the next version. ...
