Search Results for "genetic algorithm"
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Showing 19 open source projects for "genetic algorithm"
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Windocks - Docker Oracle and SQL Server ContainersWindocks is a leader in cloud native database DevOps, recognized by Gartner as a Cool Vendor, and as an innovator by Bloor research in Test Data Management. Novartis, DriveTime, American Family Insurance, and other enterprises rely on Windocks for on-demand database environments for development, testing, and DevOps. Windocks software is easily downloaded for evaluation on standard Linux and Windows servers, for use on-premises or cloud, and for data delivery of SQL Server, Oracle, PostgreSQL, and MySQL to Docker containers or conventional database instances.
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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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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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libfgen
Library for optimization using a genetic algorithm or particle swarms
libfgen is a library that implements an efficient and customizable genetic algorithm (GA). It also provides particle swarm optimization (PSO) functionality and an interface for real-valued function minimization or model fitting. It is written in C, but can also be compiled with a C++ compiler. Both Linux and Windows are supported. -
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texgenpack
Texture compression and conversion program with KTX and DDS support.
texgenpack is a texture compression and conversion program featuring a command line utility and a simple GUI program . Compression is implemented using a genetic algorithm. It supports compression, decompression, conversion and comparison of texture and image files. The image format supported is PNG, while for textures there is support for KTX, PKM and DDS using ETC1, ETC2, DXT1/3/5 or BPTC (BC7) texture compression. Several uncompressed texture format are also supported. This program requires the installation of libfgen, also avalable on SourceForge. -
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Bouc-Wen-Baber-Noori model of hysteresis
Compute parameters of the Bouc-Wen-Baber-Noori model of hysteresis
..."A Fast and Elitist multi-objective Genetic Algorithm: NSGA-II". Journal IEEE Transactions on Evolutionary Computation (IEEE-TEC). 2002. Vol. 6. No. 2. pp. 182-197. - Gilberto A. Ortiz, Diego A. Alvarez, Daniel Bedoya-Ruiz. "Identification of Bouc-Wen type models using multi-objective optimization algorithms". Computers & Structures. Vol. 114-115. pp. 121-132. 2013. -
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Alkindus is an automated solver for short monoalphabetic substitution ciphers without word divisions.
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Developed as a final year project at Islamic University of Technology (IUT) during 2010 - 2011 academic year. This code is a simple implementation of real coded genetic algorithm for numerical optimization. Code is written in C/C++.
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This library is a lightweight implementation of genetic algorithm, contains the most popular types of chromosomes and the basic algorithms for selection, elitism, crossing and mutation.
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Evolutionary Structural Optimization Package (ESOP) consists of software for viewing, analyzing, and optimizing structures containing beam, truss, and membrane plate elements utilizing OpenGL and the Genetic Algorithm (GA). Created for use in M.S. theses
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The most trusted software in constructionHCSS provides easy-to-use software built for construction companies that want to win more work, work smarter, and boost profits. For nearly 40 years, we've helped heavy civil contractors, infrastructure builders, and utility companies improve operations, from estimating and project management to field tracking, equipment maintenance, and safety. Tools like HeavyBid, HeavyJob, and HCSS Safety are built for the field and designed to work together, giving your team real-time visibility, tighter cost control, and better job outcomes. With 45+ accounting integrations and customizable APIs, HCSS fits seamlessly into your tech stack. We regularly update our software based on feedback from real crews, ensuring it fits the way your team works. Backed by award-winning 24/7/365 support and a proven implementation process, HCSS helps reduce risk, cut inefficiencies, and deliver fast ROI. If you're ready to grow your business and gain a competitive edge, HCSS is the partner that gets you there.
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Searches for adecuate design for feedforward backpropagation neural network, employing genetic algorithm as refining engine. The result topolgy may not be orthodox.
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This project aims to create an application to solve the job shop schedule problem using genetic algorithm on the IBM Cell BE processor. This is useful especially using the power of Cell for the large scale job shop schedule problem.
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A flexible programming library for evolutionary computation. Steady-state, generational and island model genetic algorithms are supported, using Darwinian, Lamarckian or Baldwinian evolution. Includes support for multiprocessor and distributed systems.
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NullAllEst is the implementation of a maximum likelihood algorithm to estimate the frequency of a null allele in microsatellite genetic data. A Markov Chain Monte Carlo simulation is used to solve the likelihood function.
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Disk Optimizer selects files to be placed on any disk medium that will maximize the space used. It is very efficient in finding an optimum file set since it uses a Genetic Algorithm instead of brute force.
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The goal of the Rats and Mazes project is to build a simple genetic algorithm to find general solutions to random non-cyclic single path mazes. I believe that the solutions will tend towards either the right/left-hand rule.
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This is a very simple implementation of the genetic algorithm framework presented by John Holland, based on Goldberg book Genetic Algorithms in Search, Optimization and Machine Learning.
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cosmos
Algorithms that run our universe | Your personal library of every algo
Cosmos (by OpenGenus Foundation) is your personal offline collection of every algorithm and data structure one will ever encounter and use in a lifetime. This provides solutions in various languages spanning C, C++, Java, JavaScript, Swift, Python, Go and others. This work is maintained by a community of hundreds of people and is a massive collaborative effort to bring the readily available coding knowledge offline.
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