Search Results for "multi objective genetic algorithm"
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Showing 31 open source projects for "multi objective genetic algorithm"
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A modern-day, loyalty rewards platform, Zinrelo helps maximize repeat sales and per-customer revenue through 360-degree customer engagement. Zinrelo encourages multiple dimensions of loyalty including transactional, social, advocacy, engagement and behavioral loyalty. It supports omni-channel deployments that span across desktop, mobile and physical stores.
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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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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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syre
Synchronous Reluctance (machines) - evolution
SyR-e is a Matlab/Octave package developed to design, evaluate and optimize synchronous reluctance and permanent magnet machines. To perform Finite Element Analysis (FEA) SyR-e is linked to FEMM software, and the simulation process (model creation, pre-processing, post-processing) is automatic and completely controlled from SyR-e code. For the design section, SyR-e embeds automatic procedures based on design equations, minimal FEA simulations or multi-objective optimization algorithm joined... -
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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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Objective Function Analysis
An alternative to neural nets for machine learning.
Objective Function Analysis models knowledge as a multi-dimensional probability density function (MD-PDF) of the perceptions and responses (which are themselves perceptions) of an entity and an objective function (OF). The learning algorithm is the action of choosing a response, given the perceptions, which maximizes the objective function. The MD-PDF is initially seeded by a uniform random number generator. The response is used to evaluate the OF and the OF is either reinforced or diminished... -
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Electronic Circuit Optimization
Optimer: a SPICE base electrical/ electronic circuit optimization tool
This project is dedicated to the optimization of (any) electrical and electronic circuits and components using evolutionary and heuristic algorithms incorporated with SPICE simulators (such as HSPICE, ngSPICE, etc.). We provide Optimer, which is a user graphical interface for circuit design and optimization. Website: https://www.circuitoptimization.com/ E-mail: contact@circuitoptimization.com/ -
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D-Tailor
D-Tailor: automated analysis and design of DNA sequences
Recent advances in DNA cloning and synthesis technologies afford high throughput implementation of designed sequences into living cells. However, our ability to design sequences to interrogate multifactorial biological processes and further engineer biological functions is lagging behind. DNA-Tailor (D-Tailor) is a fully extendable software framework for biological sequence analysis and multi-objective sequence design. D-Tailor permits the seamless integration of an arbitrary number... -
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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... -
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GA-tools
general genetic algorithms optimization fortran 95 routines
High level optimization routines in Fortran 95 for optimization problems using a genetic algorithm with elitism, steady-state-reproduction, dynamic operator scoring by merit, no-duplicates-in-population. Chromosome representation may be integer-array, real-array, permutation-array, character-array. Single objective and multi-objective maximization routines are present. Possible to incorporate own crossover and mutation operators exclusively or in addition to standard operators... -
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jMetal is an object-oriented Java-based framework for solving multi-objective optimization problems with metaheuristics.
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MicroGP
A multi-purpose extensible self-adaptive evolutionary algorithm
MicroGP (µGP, ugp) is a versatile optimizer able to outperform both human experts and conventional heuristics in finding the optimal solution of hard problems. It is an evolutionary algorithm since it mimics some principles of the Neo-Darwinian paradigm. ⚠️ A new version is available on https://github.com/squillero/microgp4 -
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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... -
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gametes
Generate complex SNP models and heterogeneous datasets
Genetic Architecture Model Emulator for Testing and Evaluating Software (GAMETES) is an algorithm for the generation of complex single nucleotide polymorphism (SNP) models for simulated association studies. GAMETES is designed to generate epistatic models which we refer to as pure and strict, that constitute the worst-case in terms of detecting disease associations, since such associations may only be observed if all n-loci are included in the disease model. User friendly GAMETES software... -
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Cyberphantom Alfa Colony
AI new tipe
This is an experimental project whose main objective is the creation of artificial intelligence (AI) new tipe. At the core of this idea is the use of special genetic algorithm that emulates the single-celled organism. The colony of such cybernetic organisms can give rise to a "reasonable" network that have a huge intellect and computing power. -
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BONESA is an open source, user-friendly interface for tuning the numerical parameters of metaheuristics. This package includes a multi-objective parameter tuning algorithm and visualizations of the performance landscape.
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MRA
A general recommender system with basic models and MRA
Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide... -
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iOVFDT
iOVFDT algorithm of incremental decision tree
... incrementally optimized very fast decision tree (iOVFDT). Inheriting the use of Hoeffding bound in VFDT algorithm for node-splitting check, it contains four optional strategies of functional tree leaf, which improve the classifying accuracy. In addition, a multi-objective incremental optimization mechanism investigates a balance among accuracy, mode size and learning speed... -
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ALCHEMY is a genotype calling algorithm for Affymetrix and Illumina products which is not based on clustering methods. Features include explicit handling of reduced heterozygosity due to inbreeding and accurate results with small sample sizes
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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... -
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Bouc-Wen-Baber-Noori model of hysteresis
Compute parameters of the Bouc-Wen-Baber-Noori model of hysteresis
... the documentation and the following papers: - Kalyanmoy Deb, Sameer Agrawal, Amrit Pratap, T Meyarivan. "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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... a population large enough to ensure the likelihood of obtaining a solution close to the DMs preferences. In this work we present a novel methodology that produces additional Pareto optimal solutions from a Pareto optimal set obtained at the end run of any multi-objective optimization algorithm. This method, which we refer to as Pareto estimation, is tested against a set of 2 and 3-objective test problems and a 3-objective portfolio optimization problem to illustrate its' utility for a real-world problem.
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ACADO Toolkit
Toolkit for Automatic Control and Dynamic Optimization
ACADO Toolkit is a software environment and algorithm collection for automatic control and dynamic optimization. It provides a general framework for using a great variety of algorithms for direct optimal control, including model predictive control, state and parameter estimation and robust optimization. ACADO Toolkit is implemented as self-contained C++ code and comes along with user-friendly MATLAB interface. The object-oriented design allows for convenient coupling of existing optimization... -
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Alkindus is an automated solver for short monoalphabetic substitution ciphers without word divisions.
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breve is a free, open-source 3D multi-agent simulation package designed for simulating decentralized systems and artificial life.
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Cambrian is a set of optimizing libraries design to optimize multi and mono objective functions. Cambrian is extension of Genetikos application developed to use genetic algorithms.