Search Results for "knapsack genetic algorithm" - Page 2
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Showing 130 open source projects for "knapsack genetic algorithm"
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tsp-problem-ga-aco-comparisson
Genetic Algorithm and Ant Colony to solve the TSP problem
This project compares the classical implementation of Genetic Algorithm and Ant Colony Optimization, to solve a TSP problem. It's possible to define the number of cities to visit , and also interactively create new cities to visit in a 2D spatial panel. A total distance is given for AG and ACO solution at end. -
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theoEA_Code
genetic algorithm for optimizing planar optical antennas
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Sched-SPM
A C++ schedule generator based on Genetic Algorithm and Hill Climbing
Sched-SPM is a C++ schedule generator for software project staffing and rescheduling based on Genetic Algorithm (GA) and Hill Climbing (HC). This preliminary tool is mainly for academic purpose. It is implemented with GALib (http://lancet.mit.edu/ga/), an open-source toolkit of Genetic Algorithms in various platforms including Unix and Windows. The input and output files of the software are required as XML format. The input file includes tasks' and employees' information according to predefined file format. ... -
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GA-EoC
GeneticAlgorithm-based search for Heterogeneous Ensemble Combinations
...To enhance classification performances, we propose an ensemble of classifiers that combine the classification outputs of base classifiers using the simplest and largely used majority voting approach. Instead of creating the ensemble using all base classifiers, we have implemented a genetic algorithm (GA) to search for the best combination from heterogeneous base classifiers. The classification performances achieved by the proposed method method on the chosen datasets are promising. -
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REDHORSE
Software suite for the analysis of haploid hybrids using NGS
...We therefore designed a software suite called REDHORSE that takes genomic alignments as input, extracts meaningful markers and generates MSAs that are the inputs to existing RD algorithms. In addition, REDHORSE implements a custom RD algorithm that makes use of sequence information and genomic positions to accurately detect crossovers. REDHORSE is portable and platform independent suite that provides efficient analysis of genetic crosses based on NGS data. -
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GeneticAlgorithms
Framework for using the Genetic Algorithms optimization heuristic.
GeneticAlgorithms is a simple and lightweight framework to implement an optimization heuristic following the Genetic Algorithms model. A genetic algorithm mimics the natural processes of evolution, selection and "survival of the fittest". This framework is intuitive and good integrated with Java 1.5 SDK and later. -
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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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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. -
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Evolutionary Nursery
A simple genetic algorithm for numerical optimization
Evolutionary nursery is a result for my passion for developing genetic algorithms. I implemented this simple GA in 2008. This is especially intended for numerical optimization problems. -
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FamSeq
Variant calling on the basis of pedigree information
...FamSeq accommodates de novo mutations and can perform variant calling at chromosome X. To accommodate variations in data complexity, FamSeq consists of three distinct implementations of the Mendelian genetic model: the Bayesian network algorithm, Elston-Stewart algorithm and Markov chain Monte Carlo algorithm. To make the software efficient and applicable to large families, we parallelized the Bayesian network algorithm that copes with pedigrees with inbreeding loops without losing calculation precision on an NVIDIA® graphics processing unit. -
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It is a C# library that implementes eight backtracking algorithms, which include Knapsack algorithm, BTKnapsack algorithm, Circles algorithm, Loading algorithm, LoadingWithIteration algorithm, Queen algorithm, NQueenWithIteration algorithm and Stamps algorithm.
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NEAT Visualizer SFML
A NEAT Implementation and Visualization System
Evolves neural networks using the Neuro-Evolution of Augmenting Topologies (NEAT) technique. A separate visualization system uses another genetic algorithm to evolve images of the otherwise dimensionless networks so their structure can be observed. -
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VariantMaster
Extract causative variants for monogenic and sporadic genetic diseases
...To improve the identification of the variants from HTS, we developed VariantMaster, an original program that accurately and efficiently extracts causative variants in familial and sporadic genetic diseases. The algorithm takes into account predicted variants (SNPs and indels) in affected individuals or tumor samples and utilizes the row (BAM) data to robustly estimate the conditional probability of segregation in a family, as well as the probability of it being de novo or somatic. In familial cases, various modes of inheritance are considered: X-linked, autosomal dominant, and recessive (homozygosity or compound heterozygosity). ... -
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niGA
Heterogenous Multiprocessor Scheduling Using Genetic Algorithms
Implementation of task scheduling using Genetics algorithm for heterogeneous parallel programming -
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Evochumps
Evolving recursive artificial neural networks in a simulation.
...It has a built-in evolutionary algorith to let the brains evolve conditoned to selective pressure. The program's interface allows you to manipulate all kinds of parameters of both the simulation, the genetic algorithm, and each particular RNN in real time. -
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PyGAO
Genetic Algorithm Optimization for Python
A simple interface for performing genetic algorithm optimization for numerical problems. I am starting with a stripped-down version, where a solution can be described using a single vector of float numbers. Eventually, I will expand to more generic data structures and add multiple-species search options. For the time being, I have no plans of developing a GUI. For now, this is strictly a computational module. -
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ABM-Calibration-SensitivityAnalysis
Codes and Data for Calibration and Sensitivity Analysis of ABM
...<http://jasss.soc.surrey.ac.uk/xx/x/x.html> Methods/Techniques used are: a. Parameter fitting: 1. Full Factorial Design 2. Simple Random Sampling 3. Latin Hypercube Sampling 4. Quasi-Newton Method 5. Simulated Annealing 6. Genetic Algorithm 7. Approximate Bayesian Computation b. Sensitivity Analysis: 1. Local SA 2. Morris Screening 3. DoE 4. Partial (Rank) Correlation Coefficient 5. Standardised (Rank) Regression Coefficient 6. Sobol' 7. eFAST 8. FANOVA Decomposition Have also a look on our other projects: http://www.uni-goettingen.de/de/315075.html -
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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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NNBrain
A free, open source collection of neural network based AI agents.
NNBrain is a free and open source collection of artificial intelligence agents. These agents have applications in video games, research, business, and more. The included agents function in both discrete and continuous action and state spaces. -
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AEvolution
Artificial life game
Artificial life game using a genetic algorithm in a simple 2D world. -
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Reactor Breeder
A Genetic Algorithm for Reactors in StarMade
This software uses a genetic algorithm to "evolve" reactor designs for Schema's space-simulation game, Star-Made (http://star-made.org/). One of the more unique aspects of the game is that ship power management is not as simple as filling a cube with power generation blocks. This mechanism leads to difficulties in getting maximal power generation out of such reactors. -
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QuasiRecomb
Probabilistic inference of viral Quasispecies
Please get the binary latest version at https://github.com/armintoepfer/QuasiRecomb/releases Description: RNA viruses are present in a single host as a population of different but related strains. This population, shaped by the combination of genetic change and selection, is called quasispecies. Genetic change is due to both point mutations and recombination events. We present a jumping hidden Markov model that describes the generation of the viral quasispecies and a method to infer its parameters by analysing next generation sequencing data. We offer an implementation of the EM algorithm to find maximum a posteriori estimates of the model parameters and a method to estimate the distribution of viral strains in the quasispecies. ... -
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Genetic Polynomials
genetic algorithm to approximate a set of points with polynomial
genetic algorithm to approximate a set of points with polynomial -
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ITS-GenTL
Traffic Lights parallel optimization software using Genetic Algorithms
ITS-GenTL - Intelligent Transport System Genetic Algorithm Traffic Lights optimizer This software is aimed to optimize traffic lights characteristics for traffic flows in urban networks in real-time using Genetic Algorithms. Now it uses SUMO project modeling software to model traffic flows while iteration of optimization process. -
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DJDarwin
A Genetic algorithm approach to creating beats.
The program puts beats through evolution - survival, mutations, reproduction. The purpose, in the words of Africa Bambaataa - Looking for the perfect beat. Using a genetic algorithmic framework, the user's taste defines a Beat fitness function - she decides which beats survive and breed, and which join the choir invisible. In addition, the user can easily define an automatic fitness function, put the program on 'autopilot' mode, and let it speed up evolution. Different types of...