As a popular optimization, particle swarm optimization has attracted many researcher's
attention and also been successfully applied to solve many real world problems. As …

As an important research direction of swarm intelligence algorithm, particle swarm
optimization (PSO) has become a popular evolutionary method and received extensive …

Particle swarm optimization (PSO) has been successfully applied to various complex
optimization problems due to its simplicity and efficiency. However, the update strategy of …

As an influential technology of swarm evolutionary computing (SEC), the particle swarm
optimization (PSO) algorithm has attracted extensive attention from all walks of life …

Particle swarm optimization (PSO) is a global optimization method that is extremely effective.
PSO's flaws include slow convergence, premature convergence, and getting stuck at local …

Particle swarm optimization (PSO) has gained increasing attention in tackling complex
optimization problems. Its further superiority when hybridized with other search techniques is …

Particle swarm optimization (PSO) is a population-based stochastic optimization that has
been widely applied to a variety of problems. However, it is easily trapped into the local …

As a new evolutionary algorithm, particle swarm optimization (PSO) achieves integrated
evolution through the information between the individuals. All the particles have the ability to …

A new class of hybrid particle swarm optimization (PSO) algorithm is developed for solving
the premature convergence caused by some particles in standard PSO fall into stagnation …