Particle swarm optimization (PSO) is one of the most commonly used stochastic optimization
algorithms for many researchers and scientists of the last two decades, and the pattern …

Particle swarm optimization (PSO) is a population-based stochastic and derivative-free
method that has been used to solve various optimization problems due to its simplicity and …

This paper presents a novel parallel Differential Evolution (DE) algorithm with local search
for solving function optimization problems, utilizing graphics hardware acceleration. As a …

This paper presents a massively parallel ant colony optimization-pattern search (ACO-PS)
algorithm with graphics hardware acceleration on nonlinear function optimization problems …

A novel particle swarm optimization with triggered mutation (PSO-TM) is presented in this
paper for better performance. First, a technique is designed to evaluate the" health" of …

In order to reduce the computational time, a fully parallel implementation of the particle
swarm optimization (PSO) algorithm on a graphics processing unit (GPU) is presented …

Band selection is a common technique to reduce the dimensionality of hyperspectral
imagery. When the desired object information is known, the reduction process can be …

Particle swarm optimization (PSO) is a bioinspired technique widely used to solve real
optimization problems. In the recent years, the use of Graphics Processing Units (GPU) has …

Particle swarm optimization (PSO) is an evolutionary heuristics-based method used for
continuous function optimization. PSO is stochastic yet very robust. Nevertheless, real-world …

The tremendous power of graphics processing unit (GPU) computing relative to prior CPU‐
only architectures presents new opportunities for efficient solutions of previously intractable …