swarm-intelligence-algorithms
There are 4 repositories under swarm-intelligence-algorithms topic.
TensorSwarm / TensorSwarm
TensorSwarm: A framework for reinforcement learning of robot swarms.
Language:Python 111- Language:Python 37
ErfanFathi / pso
This repository include implementation of particle swarm optimization (pso) algorithm in C++
Language:C++ 24arijeetsat / Glowworm-Swarm-Optimisation
Detailed Explanation and Implementation of GSO algorithm
Language:Python 15thieu1995 / 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 11nimishbongale / SpiderMonkey
This is a repository which contains all the code for the Spider Monkey Optimization Algorithm, associated with Chapter 6, Machine Learning for Intelligent Decision Science. https://link.springer.com/book/10.1007/978-981-15-3689-2
Language:Python 7sarthak268 / Swarm_Intelligence_Models
Implementation of Popular Swarm Intelligence Models
Language:Python 7- Language:Python 6
- RUN-Beyond-the-Metaphor-An-Efficient-Optimization-Algorithm-Based-on-Runge-Kutta-Method
aliasgharheidaricom / RUN-Beyond-the-Metaphor-An-Efficient-Optimization-Algorithm-Based-on-Runge-Kutta-Method
The optimization field suffers from the metaphor-based “pseudo-novel” or “fancy” optimizers. Most of these cliché methods mimic animals' searching trends and possess a small contribution to the optimization process itself. Most of these cliché methods suffer from the locally efficient performance, biased verification methods on easy problems, and high similarity between their components' interactions. This study attempts to go beyond the traps of metaphors and introduce a novel metaphor-free population-based optimization based on the mathematical foundations and ideas of the Runge Kutta (RK) method widely well-known in mathematics. The proposed RUNge Kutta optimizer (RUN) was developed to deal with various types of optimization problems in the future. The RUN utilizes the logic of slope variations computed by the RK method as a promising and logical searching mechanism for global optimization. This search mechanism benefits from two active exploration and exploitation phases for exploring the promising regions in the feature space and constructive movement toward the global best solution. Furthermore, an enhanced solution quality (ESQ) mechanism is employed to avoid the local optimal solutions and increase convergence speed. The RUN algorithm's efficiency was evaluated by comparing with other metaheuristic algorithms in 50 mathematical test functions and four real-world engineering problems. The RUN provided very promising and competitive results, showing superior exploration and exploitation tendencies, fast convergence rate, and local optima avoidance. In optimizing the constrained engineering problems, the metaphor-free RUN demonstrated its suitable performance as well. The authors invite the community for extensive evaluations of this deep-rooted optimizer as a promising tool for real-world optimization. The source codes, supplementary materials, and guidance for the developed method will be publicly available at different hubs at http://aliasgharheidari.com/RUN.html.
optimizationoptimization-algorithmsswarm-intelligence-algorithmsswarm-intelligencebenchmarkingrunge-kutta-methodsrunge-kuttamodelinggenetic-algorithmparticle-swarm-optimizationevolutionary-algorithmsevolutionary-computationevolutionary-strategydifferential-equationsdifferential-evolutionoptimization-methodsoptimization-toolsoptimization-algorithm-libraryLanguage:MATLAB 5 - Language:Python 5
trifectalabs / myriad
A Scala Akka library for swarm intelligence algorithms
Language:Scala 5betamoo / Robots-Routing-using-Swarm-Intelligence
A C# project to simulate and test a multiagent algorithm for finding multiple noisy radiation sources with spatial and communication constraints with an emulated environment. The algorithm tries to detect the source(s) of radiation with some robots in the monitoring fields. Each robot has a sensor mounted to detect the radiation concentration. The robots cooperate and communicate with each other to locate the sources based on the sensors readings using concepts from particle swarm optimization algorithm. You can see the attached paper for more detail... [Multiagent Algorithm for finding Multiple Noisy Radiation.pdf](Home_Multiagent Algorithm for finding Multiple Noisy Radiation.pdf)
Language:C# 4ChiaT27 / Artificial-Bee-Colony-Optimization
Python Implementation of the Swarm Intelligent (SI) Artificial Bee Colony Optimization Algorithm (ABC)
Language:Jupyter Notebook 4swarm-intelligence / PSO-Algorithm
Particle Swarm Optimization Implementation
Language:MATLAB 4AmeyaWagh / Hipsters_In_Swarm
Effect of hipster behavior on opinion propagation in a swarm of robots.
Language:Python 3chen0040 / cs-swarm-intelligence
Swam intelligence for numerical optimization implemented in .NET
Language:C# 3sraaphorst / dispersive-flies-optimization
A Python implementation of the Dispersive Flies Optimization algorithm, and an implementation to find Steiner systems
Language:Python 3sznczy / quantum-particle-swarm-optimization
Quantum-Behaved Particle Swarm Optimization Algorithm
Language:C++ 3Wandmalfarbe / Glowworm-Swarm-Optimization-Java
A Java implementation and visualization of the glowworm swarm optimization (GSO) algorithm invented by Krishnanand N. Kaipa and Debasish Ghose.
Language:Java 3anandi1989 / Fun-With-SOEC
Stochastic Optimization and Evolutionary Computing Algorithm implementation in python
Language:Python 2Bread-and-Code / Hive-TSP
Approaching the Travelling Salesman Problem using Hive(Beehive) simulations.
Language:Python 2GiliardGodoi / particle-swarm-optimization
An implementation of PSO
Language:Python 2- Language:Julia 2
lalit212212 / GBWPSO
Parallel Global Best-Worst Particle Swarm Optimization Algorithm for Solving Optimization Problems (Applied Soft Computing-2023)
Language:MATLAB 2Particle Swarm Optimization Implementation
Language:MATLAB 2- Language:Python 1
alexhaislip / cvg_quadrotor_swarm
🚁 Software framework for vision-based quadrotor multi-robot systems
Language:MATLAB 1banerjeesamrat / Particle-Swarm-Optimization
Dissertation project on analysis of Particle Swarm Optimization Algorithm
- Language:C++ 1
DecioXXIV / IA-Algorithms-and-Exercises
Repository per una collezione di Esercizi ed Esperimenti svolti per il corso di IA (22-23)
Language:Jupyter Notebook 0miladpayandehh / Artificial-Bee-Colony-Algorithm
Artificial bee colony (ABC) algorithm is an optimization technique that simulates the foraging behavior of honey bees, and has been successfully applied to various practical problems.
Language:MATLAB 0mBayraktar12 / PSO-Hyperparameter-Selection
Hyperparameter selection on machine learning models using Particle Swarm Optimization
Language:Python- Language:MATLAB
- Language:MATLAB
The travelling salesman problem (TSP) asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city?"
Language:MATLABSotirisFtiakas / Stochastic-Diffusion-Search-for-Feature-Selection
Implementation of the Stochastic Diffusion Search Nature-Inspired Swarm-Intelligence Optimization algorithm to solve the Curse of Dimensionality in Data Science and Machine Learning applications. This is a project for the "Optimization" module of AUTh Computer Science Department.
Language:Jupyter Notebook
