Search Results for "genetic algorithms"
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Showing 66 open source projects for "genetic algorithms"
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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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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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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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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. ... -
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This application allow user to predict dissolution profile of solid dispersion systems based on algorithms like symbolic regression, deep neural networks, random forests or generalized boosted models. Those techniques can be combined to create expert system. Application was created as a part of project K/DSC/004290 subsidy for young researchers from Polish Ministry of Higher Education.
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jMetal is an object-oriented Java-based framework for solving multi-objective optimization problems with metaheuristics.
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serein
A Framework to Model Metaheuristics
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JGAP is a Genetic Algorithms and Genetic Programming package written in Java. It is designed to require minimum effort to use, but is also designed to be highly modular. JGAP features grid functionality and a lot of examples. Many unit tests included. Legal notice/Impressum: Klaus Meffert An der Struth 25 D-65510 Idstein sourceforge <at> klausmeffert.de
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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. ... -
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Java CoreWars Evolver
A Java based, pMars compatible, CoreWars simulator with GA
A Java based, pMars compatible, CoreWars simulator with Genetic Algorithm warrior evolver functionality. Java 8 is needed. See [Wiki:Tutorial] -
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Evokit is an integrated environment for developing evolutionary computation algorithms. It is built around Java and the Eclipse platform, and will support several different libraries including ECJ.
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JAS is a java library for creating agent based simulations. It features a discrete-event time engine, APIs for network simulation design, powerful yet easy-to-use implementations of Genetic Algorithms and Neural Networks.
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JCLEC is a general purpose evolutionary computation framework developed in Java. Some of its mains features are: multilevel architecture, highly reusable and integrable with other systems, easy to use and a lot of implemented algorithms and operation
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An optimized java library for genetic algorithms. The library is designed to be fast and memory light, but still very easy to use.
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Aliza Gaming API
An extensible development framework for roleplay games.
AlizaGameAPI is a robust, open-source Java-based framework designed to streamline and enhance the development of 2D and 3D games. It offers a comprehensive set of tools, utilities, and libraries, empowering developers to create immersive and dynamic gaming experiences with ease. Key Features: Modular Architecture, Rich Graphics and UI Components, Comprehensive Game Logic and Character Management, Environment and World-Building Tools, Statistical and Mathematical Utilities, Enhanced... -
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FJSP Software
A Software for Flexible Job Shop Scheduling
Flexible job shop scheduling problem (FJSP) is very important in many fields such as production management, resource allocation and combinatorial optimization. In the real manufacturing systems, each operation could be processed on more than one machine and each machine can also process several operations. This feature is known as flexibility. You can define your problem in this software and get an optimal solution as a Gantt Chart. This software is based on my M.Sc. thesis of Shahed... -
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Search Agents - a framework for collaboration of meta-heuristic agents
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Genetic Algorithms Library (in Java)
An API for Java developers who need Genetic Algorithms
This API is intended to help developers use genetic algorithms in their own java applications. GeneticLibrary.zip contains the netbeans project of the API itself. GeneticTrial.zip contains another netbeans project which is an example explaining how to use the API. docs.zip is the documentation of the API. Please take a look there, it is really helpful. I have only two request from who will use this API; USE, UPDATE AND MODIFY IT FREELY JUST NOTE THE ORIGINAL AUTHOR -
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NaruGo is game AI project. Current targets are GO board game and Texas Holdem poker. It investigates Genetic programming to build game AI logic. Also EA/GP simulations for TSP, Graph layout and Prisoners Dilemma problem.
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HeuriStitch
An heuristic image stitcher
An heuristic image stitcher made to test Genetic and PSO based algorithms -
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GeneThello (read jə-ˈne-ˈthe-lō), is an acronym for genetic othello, an othello (reversi) playing program which based on Genetic Algorithm (GA). In principle GeneThello consist of an othello program and a genetic algorithm system.
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X-GAT (XML-based Genetic Algorithm Toolkit) is a Java framework to optimize problems with Genetic Algorithms (GAs). Differently from other frameworks, X-GAT contains ready-to-use GAs implementations and new features can be easily added.
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Awakener aims to provide a Java library for solving practical, real world optimisation problems by means of genetic algorithms (turnkey algorithms for >= 90% of industry problems). Awakener extends Sleepwalker with specific algorithms.
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Sleepwalker aims to provide a highly abstract, universal, reusable, extensible Java-based genetic algorithms framework which can be used as a basis for modelling and programming virtually any practical optimisation problem.
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EZvolve Foundation Classes
Data types and utility classes for use with evolutionary algorithms.
EZvolve Foundation Classes is a set of data types and utility classes for use with evolutionary algorithms. Currently implemented support for bit string encoding, populations, fitnesses, fitness functions, probabilities, and probability vectors.
