Particle swarm optimization (PSO) has shown its advantages in various optimization
problems. Topology and updating strategies are among its key concepts and have …

Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms
in the literature. Although the original PSO has shown good optimization performance, it still …

The particle swarm optimization (PSO) algorithm, which updates particles by considering
their past momentum and current direction, has demonstrated its power in several …

Particle swarm optimizer is a well-known efficient population and control parameter-based
algorithm for global optimization of different problems. This paper focuses on a new and …

This paper presents a new optimization algorithm–MCPSO, multi-swarm cooperative particle
swarm optimizer, inspired by the phenomenon of symbiosis in natural ecosystems. MCPSO …

Many variants with various strategies have been proposed to improve the efficiency of
Particle Swarm Optimization (PSO) algorithm. These strategies are a precious resource …

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 …

Particle swarm optimization (PSO) has been widely used to solve complex global
optimization tasks due to its implementation simplicity and inexpensive computational …

Over the ages, nature has constantly been a rich source of inspiration for science, with much
still to discover about and learn from. Swarm Intelligence (SI), a major branch of artificial …

PARTICLE swarm optimization (PSO) is one of the evo-lutionary computation techniques. It
is a population-based search algorithm and is initialized with a population of random …