metaheuristic-algorithms
There are 4 repositories under metaheuristic-algorithms topic.
Emad-Salehi / UAV-Path-Planning-using-Gray-Wolf-Optimization
Regenerated a state-of-the-art meta-heuristic algorithm for the UAV path planning problem, proposed by Qu, Gai, and Zhong.
Language:MATLAB 49Computational-Intelligence-Fall18 / Computational-Intelligence-Tutorials
This is the repository of codes written in class.
Language:Jupyter Notebook 43kkg1999 / MetaheuristicOptimization
Different meta-heuristic optimization techniques for feature selection
optimizationoptimization-algorithmsparticle-swarm-optimizationmetaheuristic-optimisationmetaheuristicsmetaheuristic-algorithmsmetaheuristic-frameworkmetaheuristicgenetic-algorithmatom-search-optimizationsailfish-optimizergolden-ratio-optimizationequilibrium-optimizersocial-mimic-optimizationmanta-ray-foraging-optimizationbarnacles-mating-optimizerLanguage:Python 37jcrvz / customhys
Customising optimisation metaheuristics via hyper-heuristic search (CUSTOMHyS). This framework provides tools for solving, but not limited to, continuous optimisation problems using a hyper-heuristic approach for customising metaheuristics. Such an approach is powered by a strategy based on Simulated Annealing. Also, several search operators serve as building blocks for tailoring metaheuristics. They were extracted from ten well-known metaheuristics in the literature.
Language:Python 17MustafaLotfi / Optimized-Inverse-Dynamics-Controller
Obtaining the best coefficients of Inverse Dynamics Controller, for a dynamical system, with Optimization Algorithms.
Language:MATLAB 15ali-ece / Design-of-optimal-CMOS-ring-oscillator-using-an-intelligent-optimization-tool
This paper presents an intelligent sizing method to improve the performance and efficiency of a CMOS Ring Oscillator (RO). The proposed approach is based on the simultaneous utilization of powerful and new multi-objective optimization techniques along with a circuit simulator under a data link. The proposed optimizing tool creates a perfect tradeoff between the contradictory objective functions in CMOS RO optimal design. This tool is applied for intelligent estimation of the circuit parameters (channel width of transistors), which have a decisive influence on RO specifications. Along the optimal RO design in an specified range of oscillaton frequency, the Power Consumption, Phase Noise, Figure of Merit (FoM), Integration Index, Design Cycle Time are considered as objective functions. Also, in generation of Pareto front some important issues, i.e. Overall Nondominated Vector Generation (ONVG), and Spacing (S) are considered for more effectiveness of the obtained feasible solutions in application. Four optimization algorithms called Multi-Objective Genetic Algorithm (MOGA), Multi-Objective Inclined Planes system Optimization (MOIPO), Multi-Objective Particle Swarm Optimization (MOPSO) and Multi-Objective Modified Inclined Planes System Optimization (MOMIPO) are utilized for 0.18-mm CMOS technology with supply voltage of 1-V. Baesd on our extensive simulations and experimental results MOMIPO outperforms the best performance among other multi-objective algorithms in presented RO designing tool.
multi-objective-optimizationpareto-optimalitypareto-frontoptimizationoptimization-algorithmsswarm-intelligenceevolutionary-algorithmsevolutionary-computationengineering-optimisationbio-inspired-optimizationheuristic-search-algorithmsmetaheuristic-optimisationmetaheuristic-algorithmsvlsi-circuitshspicematlabgabrielegilardi / PSO
Metaheuristic Minimization Using Particle Swarm Optimization.
Language:Python 9thieu1995 / IntelELM
IntelELM: A Python Framework for Intelligent Metaheuristic-based Extreme Learning Machine
classification-modelselmevolutionary-computationextreme-learning-machinegenetic-algorithmmachine-learningmetaheuristic-algorithmsnature-inspired-algorithmsneural-networksparticle-swarm-optimizationregression-modelsscikit-learnswarm-intelligence-algorithmswhale-optimization-algorithmmetaheuristic-based-extreme-learning-machinemha-elmLanguage:Jupyter Notebook 9modeling-inversion-lab / awesome-metaheuristic-algorithms
:chart_with_upwards_trend: Collect and archive the metaheuristic algorithms and their applications in geophysics.
amirabbasasadi / Babai
C++ Optimization Library
Language:C++ 7- Language:Python 6
vkotiyal / thesis-ecs-codes
Python code for ECS-NL.
Language:Jupyter Notebook 6A new optimization method based on the dynamic of sliding motion along a frictionless inclined plane. In IPO, a collection of agents cooperate with each other and move toward better positions in the search space by employing Newton’s second law and equations of motion. The standard version of the IPO is presented by Mozafari et al. in 2016. Powerful improved versions of it called MIPO and SIPO along with its multi-objective version of MOIPO were presented in 2016, 2017 and 2019 by Dr. Ali Mohammadi (myself) and colleagues at the University of Birjand, respectively. This powerful algorithm has also been used in many applications, which has provided very good outputs. In the following, the standard version of the IPO algorithm along with the benchmark functions reviewed in its reference article, and its improved versions are attached.
Language:MATLAB 5bghojogh / Metaheuristic-Optimization
The codes for metaheuristic optimization algorithms
Language:Python 5BoutainaELYAZIJI / TSP_project
The traveling salesman problem (TSP) is a well-known problem in theoretical computer science and operations research. The standard version of the TSP is a hard problem and belongs to the NP-Hard class. In this project, I build an application to implement the TSP by the dynamic approach and the GVNS approach .
Language:Python 5jonasgrebe / bees-bats-fireflies
Implementation of three nature-inspired search algorithms: Bees Algorithm, Bat Algorithm, and Firefly Algorithm
Language:HTML 5MetaPerceptron: Unleashing the Power of Metaheuristic-optimized Multi-Layer Perceptron - A Python Library
classification-modelsgenetic-algorithmglobal-searchmetaheuristic-algorithmsmetaheuristicsmlpmulti-layer-perceptronnature-inspired-optimizationneural-networkparticle-swarm-optimizationregression-modelswhale-optimization-algorithmgradient-free-based-multi-layer-perceptronmetaheuristic-based-multi-layer-perceptronadagrad-approachadam-optimizersgd-optimizeradelta-optimizerLanguage:Python 5- Language:MATLAB 4
- Language:Jupyter Notebook 4
prateekshyap / CPP-in-SDN
MATLAB simulations for Controller Placement Problem in Software Defined Networks
Language:MATLAB 4EvoRBF: A Python Library for Evolving Radial Basis Function Network by Intelligent Nature-inspired Algorithms
classificationevolutionary-algorithmsgenetic-algorithmglobal-searchgradient-free-optimizationlocal-searchmachine-learningmealpymetaheuristic-algorithmsnature-inspired-algorithmsneural-networkparticle-swarm-optimizationradial-basis-functionradial-basis-function-networkregressionswarm-intelligencewhale-optimization-algorithmgradient-free-rbfLanguage:Python 4reflame: Revolutionizing Functional Link Neural Network by Metaheuristic Optimization
flnnfunctional-link-neural-networkclassificationevolutionary-algorithmsgenetic-algorithmhigher-order-functionsmachine-learningmetaheuristic-algorithmsnature-inspired-algorithmsneural-networkparticle-swarm-optimizationpytorch-modelregressionscikit-learnfunctional-link-artificial-neural-networkhigher-order-neural-networkfeed-forward-neural-networksoptimization-algorithmsshadewhale-optimization-algorithmLanguage:Python 4With the aim of create a powerful trade-off between the concepts of exploitation and exploration, and rectify the complexity of their structural parameters in the standard IPO, a modified version of IPO (called MIPO) is introduced as an efficient optimization algorithm for digital infinite-impulse-response (IIR) filters model identification. The MIPO utilizes an appropriate mechanism based on the executive steps of algorithm with the constant damp factors.
Language:MATLAB 3chasebk / code_ISLO_ELM
A study on swarm intelligence optimizing neural networks for workload elasticity prediction
Language:Jupyter Notebook 3xjcheam / portfolio-optimization-qts-trend-ratio
This is a project of portfolio optimization using Quantum-inspired Tabu Search and Trend Ratio
Language:Python 3arawxx / PSO-demonstration
Demonstration of Particle Swarm Optimization (Auto Hyperparameter variant).
Language:Python 2CasillasAlba / Big-Bang-Big-Crunch
Final project for Methaeuristics subject, taught at the University of Granada during the 2019/2020 academic year.
Language:Python 2- godon
cherusk / godon
(ancient german = improving, rearranging, rendering benign)
optimization-algorithmsoptimizationdaemonaiopsgenetic-algorithmscontrol-systemsevolutionary-algorithmsinfrastructureself-improvementperformance-tuningconfiguratorfeedback-loopcontinuous-optimizationperformancegenetic-optimization-algorithmserviceevolutionary-computationmetaheuristicsmetaheuristic-algorithmscloudLanguage:Python 2 KentaKato / SpyOpt
C++ implementation of the metaheuristic spy_algorithm. It can search for global optimal solutions for arbitrary non-convex functions.
Language:C++ 2mateuszlesko / GenericAlgoirthm
Implementation of Generic Algorithm
Language:Java 2MichaelisTrofficus / pyheuristics
A toolkit for MetaHeuristics implemented in Python
Language:Python 2toohidsharifi / Optimal-design-of-Permanent-Magnet-Synchronous-Motor
Optimal Design of a Permanent Magnet Synchronous Motor Using the Cultural Algorithm
ansys-electronics-desktopcultural-algorithmdesign-optimizationmatlabmetaheuristic-algorithmsmetaheuristicsoptimizationoptimization-algorithmspermanent-magnet-synchronousansys-maxwellcoupled-simulationelectric-motor-optimizationinterface-ansys-matlabsynchronous-motortorque-densitytorque-improvementtorque-performanceconstrained-optimizationelectric-vehiclestransportation-electrification- Language:Java 2
boatzaa1456 / Project-Set-Based-Mayfly-Algorithm-for-Solving-Order-Batching-Problems
This research proposes a novel order batching approach for warehouses to minimize total tardiness, considering category, weight, and fragility constraints. A Set-based Mayfly Algorithm (SBMA) is developed, adapting the Mayfly Algorithm to the discrete problem and leveraging swarming/mating behaviors to avoid local optima.
Language:Python 1jhadziahDev / Diverse-Protein-Discovery-in-Large-Scale-Datasets-A-Machine-Learning-Perspective
This work was aimed at finding methods to identify the most distant proteins and most diverse subsets of proteins from large protein databases in a scalable and efficient way using a dataset of protein embeddings from SwissProt, data mining techniques and metaheuristics.
Language:Python 1
