Wednesday, 2 September 2020

MATLAB code of Particle swarm optimization | Search based optimization

Hello, Guys today i would like to post one project in the field of Optimization. The post is about MATLAB implementation of Particle swarm Optimization. PSO was developed by Kennedy and Eberhart. The PSO is inspired by the social behavior of a flock of migrating birds trying to reach an unknown destination. In PSO, each solution is a ‘bird’ in the flock and is referred to as a ‘particle’. A particle is analogous to a chromosome (population member) in GAs. As opposed to GAs, the evolutionary process in the PSO does not create new birds from parent ones. Rather, the birds in the population only evolve their social behavior and accordingly their movement towards a destination.

YouTube Video of the Project: 
 

The PSO is one of the contemporary meta-heuristic population-based stochastic optimizations that is carried out on noncontinuous and nonlinear optimization problems. It delivers an evolutionary-based search to discover the near-optimal/optimal solutions. The PSO behavior is envisioned from the searching strategy for optimal food sources by the bird swarms.

Algorithm: 
Start
Initialize - The position and velocity of the particles
Determine -  Stopping criteria
Access - The each particle’s fitness using the objective function
Update - The individual/global best positions and finesses
Update - Position/velocity of each particle
Stop

MATLAB Implementation of the PSO:

Fig: Main MATLAB GUI of PSO

Fig:  MATLAB GUI of PSO

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