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 …

In recent years, particle swarm optimization (PSO) has been extensively applied in various
optimization problems because of its structural and implementation simplicity. However, the …

In order to overcome the several shortcomings of Particle Swarm Optimization (PSO) eg,
premature convergence, low accuracy and poor global searching ability, a novel Simple …

In recent years, particle swarm optimization (PSO) algorithm has been used to solve global
optimization problems. This algorithm is widely used as an effective optimization tool in …

Particle Swarm Optimization (PSO) is a recently developed optimization method, which has
attracted interest of researchers in various areas due to its simplicity and effectiveness, and …

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) algorithm has the ability of global optimization, but it often
suffers from premature convergence problem, especially in high-dimensional multimodal …

Particle swarm optimization (PSO) has been invented by inspiring social behaviors of fish or
birds to solve nonlinear global optimization problems. Since its invention, many PSO …

In this paper, we introduce the concept of population density in PSO, and accordingly, we
discuss the relationship between the search capability of PSO and the population density …

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 …