Search Results for "genetic algorithm delphi"
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Showing 9 open source projects for "genetic algorithm delphi"
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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). A Blazor... -
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This site hosts the source code for C++ version of the Broker for SBW, NOM module, advanced simulation suite, analysis applications and model editors.
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AppM Build Automation
Automated software application for constructing and building projects.
AppM Build Automaiton is an open source and automated software application that is used to construct and build projects on different operating systems and using different development environments. General principles of implementation: -Each project must have a Build Project File, containing the necessary information on the construction of the project. For example, a unique name of the project, dependence on other projects and libraries, methods of construction, etc. Thus, the entire... -
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Game Toolbox is a C# assembly designed to facilitate the creation of games and game prototypes. It contains no graphics code, does not depend on XNA, and is Mono-compatible. It provides implementations of A*, GOAP, a genetic algorithm, and more.
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DrCrypt, based on basic xor(exclusive or) encryption which is designed to be fast and reliable. Also DrCrypt supports 3 platform.(Java, .NET, Win32)
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A .net implementation of a framework for genetic algorithms. This tool enables programmers to write the "core" of their problem and have a genetic algorithm immediately setup for solving it.
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In this project we develop a software, that uses evolutionary algorithm to evolve a solution, that can drive a car on an arbitrari path.
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GEP is an evolutionary algorithm for function finding. This framework is a powerful way of expressing and coding genetic-like structures and quickly finding solutions through evolution by common genetic operators.
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Application to test a GA solution for the Knapsack problem, it will compare Genetic Algorithm solution of the Knapsack problem to greedy algorithm.
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