Search Results for "binary differential evolution"
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Showing 10 open source projects for "binary differential evolution"
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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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PlatEMO
Evolutionary multi-objective optimization platform
...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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React Native Module for CodePush
React Native module for CodePush
This plugin provides client-side integration for the CodePush service, allowing you to easily add a dynamic update experience to your React Native app(s). A React Native app is composed of JavaScript files and any accompanying images, which are bundled together by the packager and distributed as part of a platform-specific binary (i.e. an .ipa or .apk file). Once the app is released, updating either the JavaScript code (e.g. making bug fixes, adding new features) or image assets, requires... -
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The ASCO project aims to bring circuit optimization capabilities to existing SPICE simulators using a high-performance parallel differential evolution (DE) optimization algorithm. It supports Eldo, HSPICE, LTspice, Spectre, and Qucs.
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scikit-opt
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing
scikit-opt is a Python library for solving optimization problems with evolutionary and swarm-intelligence algorithms. It includes genetic algorithms, particle swarm optimization, differential evolution, simulated annealing, ant colony optimization, immune algorithms, and artificial fish swarms. The package can address continuous objectives, constrained problems, and combinatorial tasks such as the traveling salesman problem. A consistent workflow lets users define an objective, configure an optimizer, run iterations, and inspect the best solution. ... -
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OpenDino
Open Source Java platform for Optimization, DoE, 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 other programs (solvers) - parallel execution of problems - distributed execution of problems via socket connection between computers Others: - data storage - data analyser and viewer -
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Point Symmetry Clustering
Point Symmetry Clustering Approach Using Differential Evolution
Implementation of Point Symmetry-based Automatic Clustering Approach Using Differential Evolution Using bug fixed KD tree nearest neighbor search from https://github.com/CristianDallos/kmeansclustering. (It is also modified to search for multiple nearest points instead only for one.) Used those academic works for algorithm implementation: http://cs.cug.edu.cn/teacherweb/gwy/Publication/ISICA-09.pdf http://www.isical.ac.in/~sanghami/ieeetkde_cameraready.pdf http://www.softcomputing.net/smca-paper1.pdf 1. ... -
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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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MOEA Framework
A Free and Open Source Java Framework for Multiobjective Optimization
The MOEA Framework is a free and open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose multiobjective optimization algorithms. The MOEA Framework supports genetic algorithms, differential evolution, particle swarm optimization, genetic programming, grammatical evolution, and more. A number of algorithms are provided out-of-the-box, including NSGA-II, NSGA-III, ε-MOEA, GDE3 and MOEA/D. In addition, the MOEA Framework provides the tools necessary to rapidly design, develop, execute and statistically test optimization algorithms. -
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Library for creation of artificial neural networks in C#. Library supports Hopfield nets, Kohonen nets, feedforward networks, several learning techniques (differential evolution, back propagation, quick propagation, resilient propagation etc.)
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