Particle Swarm Optimization (PSO) is a well-known extensively utilized algorithm for a
distinct type of optimization problem. In meta-heuristic algorithms, population initialization …

Particle swarm optimization (PSO) algorithm is a population‐based intelligent stochastic
search technique used to search for food with the intrinsic manner of bee swarming. PSO is …

Metaheuristic algorithms have been widely used to solve diverse kinds of optimization
problems. For an optimization problem, population initialization plays a significant role in …

Particle Swarm Optimization (PSO) has been frequently employed to solve diversified
optimization problems. Choosing initial placement for population plays an important role in …

This study proposes a novel Integrated Learning Particle Swarm Optimizer (ILPSO), for
optimizing complex multimodal functions. The algorithm modifies the learning strategy of …

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 …

Stochastic optimization algorithms like genetic algorithms (GAs) and particle swarm
optimization (PSO) algorithms perform global optimization but waste computational effort by …

Premature convergence has been recognized as one of the major drawbacks of particle
swarm optimization (PSO) algorithms. In particular, the lack of diversity in PSO performance …

In recent years, particle swarm optimization (PSO) has extensively applied in various
optimization problems because of its simple structure. Although the PSO may find local …

Since canonical PSO method has many disadvantages which do not allow to effectively
reach the global minima of various functions it needs to be improved. The article refers to a …