Particle swarm optimization (PSO) is considered one of the most important methods in
swarm intelligence. PSO is related to the study of swarms; where it is a simulation of bird …

This paper introduces a novel parameter automation strategy for the particle swarm
algorithm and two further extensions to improve its performance after a predefined number …

This paper presents an overview of our most recent results concerning the Particle Swarm
Optimization (PSO) method. Techniques for the alleviation of local minima, and for detecting …

Particle swarm optimization is a recently invented high-performance optimizer that is very
easy to understand and implement. It is similar in some ways to genetic algorithms or …

This paper presents approaches for effectively computing all global minimizers of an
objective function. The approaches include transformations of the objective function through …

SOCIETY. To become official, the name needs to be approved by the Board of Directors
which is expected to meet on June 20, 2004. As many of you may remember, the motion to …

In this correspondence, an approach based on coevolutionary particle swarm optimization to
solve constrained optimization problems formulated as min-max problems is presented. In …

Although the particle swarm optimisation (PSO) algorithm requires relatively few parameters
and is computationally simple and easy to implement, it is not a globally convergent …

Minimax optimization is a widely-used formulation for robust design in multiple operating or
environmental scenarios, where the worst-case performance among multiple scenarios is …

We introduce a new algorithm for fuzzy cognitive maps learning. The proposed approach is
based on the particle swarm optimization method and it is used for the detection of proper …