Mathematical optimization

Hybrid particle swarm optimization and gravitational search algorithm (psogsa) in matlab

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).

Differential search algorithm a modernized particle swarm optimization algorithm in matlab

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.

Particle swarm optimization in matlab

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.

Genetic Algorithm Matlab Code

Genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems.[1] Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.

genetic algorithm

Functional optimization of non linear function using genetic algorithm in matlab

The following Matlab project contains the source code and Matlab examples used for functional optimization of non linear function using genetic algorithm. Functional Optimization Of Non linear Function(y=sinx) using Genetic Algorithm. Crossover and mutation are used to generated the other chromosomes. This is repeated for generations to get the maximum value of the nonlinear function.

Model determination using genetic algorithm application to vapour pressure vs temperature equations in matlab

The following Matlab project contains the source code and Matlab examples used for model determination using genetic algorithm application to vapour pressure vs temperature equations. We use the genetic algorithm (gatool) to determine the three parameters of the simple Antoine equation and the six parameters of the Modified Antoine Model.

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