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 …

Meta-heuristic algorithms have a high position among academic researchers in various
fields, such as science and engineering, in solving optimization problems. These algorithms …

Stochastic configuration network (SCN), as a novel incremental generation model with
supervisory mechanism, has an excellent superiority in solving large-scale data regression …

This research's genesis is in two aspects: first, a guaranteed solution for mitigating the grey
wolf optimizer's (GWO) defect and deficiencies. Second, we provide new open-minding …

The slime mould algorithm (SMA) is a logical swarm-based stochastic optimizer that is easy
to understand and has a strong optimization capability. However, the SMA is not suitable for …

Nature-inspired optimization algorithms can solve different engineering and scientific
problems owing to their easiness and flexibility. There is no need for structural modifications …

The shuffled frog lea** algorithm is a new optimization algorithm proposed to solve the
combinatorial optimization problem, which effectively combines the memetic algorithm …

In order to improve the penetration of renewable energy resources for distribution networks,
a joint planning model of distributed generations (DGs) and energy storage is proposed for …

Pulmonary hypertension (PH) is an uncommon yet severe condition characterized by
sustained elevation of blood pressure in the pulmonary arteries. The delaying treatment can …

Abstract Grey Wolf Optimizer (GWO) is a new swarm intelligence algorithm mimicking the
behaviours of grey wolves. Its abilities include fast convergence, simplicity and easy …