Particle Swarm Optimization

An animated simulation of Particles in 2D searching for a global minima of a simple function using Particle Swarm Optimization algorithm

Particle swarm optimization is a technique used in many control systems application. Here i used the PSO in PID controller tuning

This upload contains a hybrid Particle Swarm Optimization algorithm for functions in the real space. An options file is also provided, which lets the user fully parameterize the process. The hybrid function used is the @fminsearch, which is available on the MATLAB core. The PSO performs very well...


Platforms: Matlab

The Particle Swarm Optimization Research Toolbox was written to assist with thesis research combating the premature convergence problem of particle swarm optimization (PSO). The control panel offers ample flexibility to accommodate various research directions. After specifying your intentions,...


Platforms: Matlab

Particle swarm optimization (PSO) is one of the modern heuristic algorithms that can be applied to continuous and discrete optimization problems.The original binary PSO (BPSO) has got some disadvantages that make the algorithm not to converge well.To deal with these disadvantages, a new BPSO...


Platforms: Matlab

Robust Particle Swarm toolbox implementing Trelea, Common, and Clerc types along with an alpha version of change detection.This toolbox is designed for researchers in Computational Intelligence as well as application developers, students, and classroom labs. It is robust enough that several...


Platforms: Matlab

Particle Swarm Optimization toolkit (with GUI) - Allows you to implement PSO algorithm for optimization of engineering/finance/management systems.


Platforms: Windows, Mac, Linux

Particle swarm optimization is a derivative-free global optimum search algorithm based on the collective intelligence of a large group of intercommunicating entities. The individual particles are simple and primitive, knowing only their own current locations and fitness values, their personal...


Platforms: Matlab

Implements various optimization methods which do not use the gradient of the problem being optimized, including Particle Swarm Optimization, Differential Evolution, and others. The implementation is simple and easy to understand.Also included are parallel versions of PSO and DE, as well as...


Platforms: Matlab

A new hybrid population-basedalgorithm (PSOGSA) is proposed with the combination ofParticle Swarm Optimization (PSO) and Gravitational SearchAlgorithm (GSA). The main idea is to integrate the ability ofexploitation in PSO with the ability of exploration in GSA tosynthesize both algorithmsd-deOao...


Platforms: Matlab

Base paper detail : "Improved Particle Swarm Optimization Based Load Frequency Control In A Single Area Power System"Saumya Kr. Gautam, Nakul Goyal Department of Electrical Engineering, IT-BHUVaranasi,India."This my first model, implementing IPSO/ Other Algorithm i will publish soon"


Platforms: Matlab

A few popular metaheuristic algorithms are included, such as the particle swarm optimization, firefly algorithm, harmony search and others.


Platforms: Matlab

This is an accelerated PSO (APSO), developed by Xin-She Yang in 2008. APSO does not use velocities or any inertia parameter.A full program for solving nonlinear constrained optimization problem (welded beam design as an example) is provided, which can be extended to solve other continuous...


Platforms: Matlab

A flexible implementation of PSO algorithm with time-varying parameters. Algorithm is suitable for solving continuous optimization problems. Special care has been taken to enable flexibility of the algorthm with respect to its parameters and to initial population selection. Detailed logging of...


Platforms: Matlab

An attempt to design minimum cost broadband networks with the use of a modified version of the Particle Swarm Optimization method. A GIS subsystem is used for the visualization of data and results.


Platforms: Windows, Mac, Linux

The program is writing base on the principle of the PSO algorithm,and it is used to Water quality model calibration. I have modified the program for many times ,and it is the final program I have used to calibrate the parameter oh the streeter-phelps water quality model.


Platforms: Matlab

My work has been accepted in GECCO 2008 as Graduate Student workshop. I have used this technique in PID tunning and i got better result than BG and PSO


Platforms: Matlab

It finds the minimum of a n variables function with the Particle Swarm Optimization Algorithm.% The input parameters are:% -func: it's the objective function's handle to minimize% -numInd: it's the number of the swarm's elements% -range: it's the range in which the elements must be created%...


Platforms: Matlab

This add-in to the PSO Research toolbox (Evers 2009) aims to allow an artificial neural network (ANN or simply NN) to be trained using the Particle Swarm Optimization (PSO) technique (Kennedy, Eberhart et al. 2001).This add-in acts like a bridge or interface between MATLABd-deOaos NN toolbox and...


Platforms: Matlab

In the global optimization and GADS toolboxes, "ackleyfcn.m" implements a different Ackley formulation than what is commonly used in optimization literature. For those who prefer the traditional benchmark formulation, this fix modifies the Ackley code of the Particle Swarm Optimization Research...


Platforms: Matlab