# Steady state genetic algorithm with subpopulation in c

The following C project contains the C source code and C examples used for steady state genetic algorithm with subpopulation. GAS is a steady state genetic algorithm with subpopulation support.

The following C project contains the C source code and C examples used for simple math functions. This application gives you the surface of a cube, square, and circle it also gives you the hypotinuse of a right triangle. its real ez to use just check it out and see

The following Matlab project contains the source code and Matlab examples used for 1+1 evolution strategy (es).
This algorithm implements the simplest of all "evolution strategies" (ES), the (1+1)-ES.

The following Matlab project contains the source code and Matlab examples used for multi objective optimization using evolution strategies (es) as evolutionary algorithm (ea).
This function uses Evolution Strategies (ES) instead of Genetic Algorithms (GA) as Evolutionary Algorithm (EA) in the NSGA-II procedure for multi-objective optimization.

The following Matlab project contains the source code and Matlab examples used for multi objective differential evolution algorithm with spherical pruning based on preferences.
This code implements a version of the multi-objective differential evolution algorithm with spherical pruning based on preferences (spMODE-II, second version of the spMODE algorithm) described in:
Gilberto Reynoso-Meza.

The following Matlab project contains the source code and Matlab examples used for multi objective optimization differential evolution algorithm.
This Toolset comprises of the following files:
1) MODEparam.

Particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the search-space according to simple mathematical formulae over the particle's position and velocity.

The following Matlab project contains the source code and Matlab examples used for multi objective optimization, particle swarm algorithm zdt, kur, sch .
Improved many target particle swarm algorithm, success in solving the multi-objective optimization of the classic problems, such as ZDT, KUR, SCH classic optimization problem, only to f1 and f2 function after modification can be used.

The following Matlab project contains the source code and Matlab examples used for pso for global optimization problems.
Particle Swarm Optimization is a simplified social system with swarm intelligence.

The following Matlab project contains the source code and Matlab examples used for finding pid controllers gain using particle swarm optimization.
In this, i have used two dimensional search method for finding the Kp, Ki gain values

The following Matlab project contains the source code and Matlab examples used for tunning of pid controller using bacterial foraging orientec by particle swarm optimization.
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

The following Matlab project contains the source code and Matlab examples used for hybrid particle swarm optimization and gravitational search algorithm (psogsa).
A new hybrid population-based algorithm (PSOGSA) is proposed with the combination of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA).

The following Matlab project contains the source code and Matlab examples used for enhanced binary particle swarm optimization (bpso) with 6 new transfer functions.
This work includes 8 different versions of Binary Particle Swarm optimization (BPSO) algorithm.

The following Matlab project contains the source code and Matlab examples used for differential search algorithm a modernized particle swarm optimization algorithm.
Differential Search Algorithm (DSA) is a new and effective evolutionary algorithm for solving real-valued numerical optimization problems.

The following Matlab project contains the source code and Matlab examples used for optimal reactive power dispatch(orpd) using particle swarm optimization(pso).
I have solved the optimal reactive power dispatch problem using Particle Swarm Optimization algorithm for IEEE 30 bus test system.

The following Matlab project contains the source code and Matlab examples used for particle swarm optimisation augmented.
This is a version of Wesam Elshamy's PSO code that can be put to general use on any objective function.

The following Matlab project contains the source code and Matlab examples used for nbpso (new binary particle swarm optimization) algorithm.
Particle swarm optimization (PSO) is one of the modern heuristic algorithms that can be applied to continuous and discrete optimization problems.

The following Matlab project contains the source code and Matlab examples used for tunning of pid controller using particle swarm optimization.
Particle swarm optimization is a technique used in many control systems application. Here i used the PSO in PID controller tuning

The following Matlab project contains the source code and Matlab examples used for autonomous groups particles swarm optimization (agpso).
A modified particle swarm optimization (PSO) algorithm called autonomous groups particles swarm optimization (AGPSO) is proposed to further alleviate the two problems of trapping in local minima and slow convergence rate in solving high-dimensional problems.

The following Matlab project contains the source code and Matlab examples used for optimization griewangk function by particle swarm optimization.
The zip include four files
PSO31.m main PSO funtion with detailed comment.
PlotG.m is used to visulize the Griewangk Function.
Griewangk.m is the Griewangk Function itself.

The following Matlab project contains the source code and Matlab examples used for convergent heterogenous particle swarm optimization.
In CHPSO, there are four cooperative sub-swarms that can share information from each other but maintain differences.

The following Matlab project contains the source code and Matlab examples used for particle swarm optimization, differential evolution.
Implements various optimization methods which do not use the gradient of the problem being optimized, including Particle Swarm Optimization, Differential Evolution, and others.

The following Matlab project contains the source code and Matlab examples used for particle swarm optimization (pso) algorithm.
A flexible implementation of PSO algorithm with time-varying parameters.

The following Matlab project contains the source code and Matlab examples used for particle swarm optimization (vectorized code).
Particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality.

The following Matlab project contains the source code and Matlab examples used for particle swarm optimization research toolbox.
The Particle Swarm Optimization Research Toolbox was written to assist with thesis research combating the premature convergence problem of particle swarm optimization (PSO).

The following Matlab project contains the source code and Matlab examples used for optimization using particle swarm.
A set of codes used for finding minimum of a problem.

The following Matlab project contains the source code and Matlab examples used for a pso (particle swarm optimization)program .
The program is writing base on the principle of the PSO algorithm,and it is used to Water quality model calibration.

The following Matlab project contains the source code and Matlab examples used for particle swarm optimization .
PSO(particle swarm optimization) one of nature inspired techniques is used to optimize the objective function in MUD.

The following Matlab project contains the source code and Matlab examples used for particle swarm optimization toolbox.
The most basic code of PSO has been presented here.

The following Matlab project contains the source code and Matlab examples used for particle swarm optimization.
fun: function handle (y = fun(x), x is column vector)
np: number of particles
lb, ub: lb<x<ub
xMin: yMin = fun(xMin)
yMin: minimum value of the cost function fun
pso finds the global minimum for a constraint function (convex or non-con) with multiple variables.