Stochastic optimization algorithms like genetic algorithms (GAs) and particle swarm
optimization (PSO) algorithms perform global optimization but waste computational effort by …

This paper presents a new variant of Particle Swarm Optimization algorithm named QPSO
for solving global optimization problems. QPSO is an integrated algorithm making use of a …

The general purpose optimization method known as Particle Swarm Optimization (PSO) has
a number of parameters that determine its behaviour and efficacy in optimizing a given …

This paper present the hybrid approaches of Particle Swarm Optimization (PSO) with
Genetic Algorithm (GA). PSO and GA are population based heuristic search technique which …

In this paper, a new particle swarm optimisation algorithm, called MeanPSO, is presented,
based on a novel philosophy by modifying the velocity update equation. This is done by …

Optimization is a mathematical technique that concerns the finding of maxima or minima of
functions in some feasible region. There is no business or industry which is not involved in …

The particle swarm optimization algorithm includes three vectors associated with each
particle: inertia, personal, and social influence vectors. The personal and social influence …

Purpose–Meta-heuristic algorithms are efficient in achieving the optimal solution for
engineering problems. Hybridization of different algorithms may enhance the quality of the …

The Particle Swarm Optimization (PSO) method is a well-established technique for global
optimization. During the past years several variations of the original PSO have been …

Particle swarm optimization (PSO) is a population-based optimization technique that has
been applied extensively to a wide range of engineering problems. This paper proposes a …