What purpose is particle swarm optimization used?

What purpose is particle swarm optimization used?

APSO can perform global search over the entire search space with a higher convergence speed. It enables automatic control of the inertia weight, acceleration coefficients, and other algorithmic parameters at the run time, thereby improving the search effectiveness and efficiency at the same time.

Is particle swarm optimization nature inspired algorithm?

Particle swarm optimization (PSO) is a nature-inspired algorithm that has shown outstanding performance in solving many realistic problems.

Who proposed particle swarm optimization?

Kennedy and Eberhart
The particle swarm optimization (PSO) algorithm, proposed by Kennedy and Eberhart [1], is a metaheuristic algorithm based on the concept of swarm intelligence capable of solving complex mathematics problems existing in engineering [2].

How does particle swarm optimization work?

In computational science, 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. It solves a problem by having a population of candidate solutions, here dubbed particles,…

What is Adaptive particle swarm optimization?

Adaptive particle swarm optimization (APSO) features better search efficiency than standard PSO . APSO can perform global search over the entire search space with a higher convergence speed.

What is velocity in particle swarm optimization?

Velocity in the Particle Swarm Optimization algorithm (PSO) is one of its major features, as it is the mechanism used to move (evolve) the position of a particle to search for optimal solutions . The velocity is commonly regulated, by multiplying a factor to the particle’s velocity.

What is binary particle swarm optimization?

Binary particle swarm optimization (BPSO) The particle swarm optimization (PSO) is a robust stochastic optimization technique based on the movement and intelli- gence of swarms. PSO is a population-based search algorithm based on simulation of the social behavior of birds within a flock [5].