Particle Swarm Optimization for Single Objective Continuous Space Problems: A Review Page 1
Particle Swarm Optimization for Single Objective Continuous Space Problems: A Review …

Almost all real-world optimisation problems are constrained. Solving constrained problems
is difficult for optimisation techniques. In this paper, different constraint handling strategies …

Electrical power systems are evolving from today's centralized bulk systems to more
decentralized systems. Penetrations of renewable energies, such as wind and solar power …

In their original versions, nature-inspired search algorithms such as evolutionary algorithms
and those based on swarm intelligence, lack a mechanism to deal with the constraints of a …

Optimization techniques inspired by swarm intelligence have become increasingly popular
during the last decade. They are characterized by a decentralized way of working that …

During the past decade, hybrid algorithms combining evolutionary computation and
constraint-handling techniques have shown to be effective to solve constrained optimization …

Hybrid Electric Vehicles (HEV) combine the power from an electric motor with that from an
internal combustion engine to propel the vehicle. The HEV electric motor is typically …

In this correspondence, an approach based on coevolutionary particle swarm optimization to
solve constrained optimization problems formulated as min-max problems is presented. In …

Differential Search method is recently proposed to solve box constrained global optimization
problems. In this paper, we will further extend this method to solve generalized constrained …

Wind turbine (WT) condition monitoring and anomaly detection based on Supervisory
Control and Data Acquisition (SCADA) data are helpful for wind power operators to organize …