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 …

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 …

Particle swarm optimization is a novel swarm-intelligence-based algorithm and a valid
optimization technique. However, the algorithm suffers from the premature convergence …

Particle swarm optimization (PSO) is a population based algorithm for solving global
optimization problems. Owing to its efficiency and simplicity, PSO has attracted many …

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

Autonomous groups of particles swarm optimization (AGPSO), inspired by individual
diversity in biological swarms such as insects or birds, is a modified particle swarm …

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 …

Particle swarm optimization (PSO) is a relatively new optimization algorithm that has been
applied to a variety of problems. However, it may easily get trapped into local optima when …

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

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 …