We consider the problem of using wireless sensor networks (WSNs) to measure the
temporal-spatial field of some scalar physical quantities. Our goal is to obtain a sufficiently …

In agile methods, software products are developed in several releases. In each release, a
new set of requirements for development is proposed. Due to technical and non-technical …

Particle swarm optimization (PSO) is a population-based metaheuristic optimization
algorithm that solves a problem through iterative operations. Traditional PSO iteration …

This article presents a performance study on the effect of synchronicity in communications
and neighborhood size in Particle Swarm Optimization (PSO) on large-scale optimization …

In this work the well-known Particle Swarm Optimization (PSO) algorithm is applied to some
Dynamic Optimization Problems (DOPs). The PSO algorithm is improved by simplification …

The design of high-performing robotic controllers constitutes an example of expensive
optimization in uncertain environments due to the often large parameter space and noisy …

In the original particle swarm optimization algorithm, particles' update is done
synchronously. The whole swarm fitness is evaluated first before particle update process is …

Evolutionary algorithms are suitable methods for solving complex problems. Many changes
have thus been made on their original structures in order to obtain more desirable solutions …

Recently, the transmission dynamics of the Human Papillomavirus (HPV) has been studied.
In previous works, we have designed and implemented a computational model (agent …

In the original particle swarm optimisation (PSO) algorithm, the particles' velocities and
positions are updated after the whole swarm performance is evaluated. This algorithm is …