Like most evolutionary algorithms, particle swarm optimization (PSO) usually requires a
large number of fitness evaluations to obtain a sufficiently good solution. This poses an …

Particle swarm optimization (PSO) has been proved to be an effective tool for function
optimization. Its performance depends heavily on the characteristics of the employed …

Many optimization problems in reality have become more and more complex, which promote
the research on the improvement of different optimization algorithms. The particle swarm …

In this paper, a Multi-Swarm Self-Adaptive and Cooperative Particle Swarm Optimization
(MSCPSO) based on four sub-swarms is presented. In the proposed algorithm, several …

Abstract Particle Swarm Optimization (PSO) algorithm has lately received great attention due
to its powerful search capacity and simplicity in implementation. However, previous studies …

Particle swarm optimization (PSO) is one of the well-known population-based techniques
used in global optimization and many engineering problems. Despite its simplicity and …

Over the last two decades, the newly developed optimization technique–Particle Swarm
Optimization (PSO) has attracted great attention. Two common criticisms exist. First, most …

Particle swarm optimization (PSO) is a population-based optimization technique that can be
applied to a wide range of problems. Here, we first investigate the behavior of particles in the …

The particle swarm optimization (PSO) algorithm is a new population based search strategy,
which has exhibited good performance on well-known numerical test problems. However …

Particle swarm optimization (PSO) is a population-based stochastic search technique for
solving optimization problems over continuous space, which has been proven to be efficient …