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 …

Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm
motivated by intelligent collective behavior of some animals such as flocks of birds or …

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 …

This study proposes a bald eagle search (BES) algorithm, which is a novel, nature-inspired
meta-heuristic optimisation algorithm that mimics the hunting strategy or intelligent social …

The first powerful variant of the Harris hawks optimization (HHO) is proposed in this work.
HHO is a recently developed swarm-based stochastic algorithm that has previously shown …

A comprehensive learning particle swarm optimizer (CLPSO) embedded with local search
(LS) is proposed to pursue higher optimization performance by taking the advantages of …

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

The Particle Swarm Optimisation (PSO) algorithm was inspired by the social and biological
behaviour of bird flocks searching for food sources. In this nature-based algorithm …

This paper has been contributed on the basis of three main goals, namely, to identify the
research gaps, challenges and open issues in the academic literature related to the …

There are two common challenges in particle swarm optimization (PSO) research, that is,
selecting proper exemplars and designing an efficient learning model for a particle. In this …