Now showing items 1-6 of 6
A memetic particle swarm optimization algorithm for multimodal optimization problems.
(Elsevier B.V., 2012)
Recently, multimodal optimization problems (MMOPs) have gained a lot of attention from the evolutionary algorithm (EA) community since many real-world applications are MMOPs and may require EAs to present multiple optimal ...
A survey of swarm intelligence for dynamic optimization: Algorithms and applications
Swarm intelligence (SI) algorithms, including ant colony optimization, particle swarm optimization, bee-inspired algorithms, bacterial foraging optimization, firefly algorithms, fish swarm optimization and many more, have ...
Force-imitated particle swarm optimization using the near-neighbor effect for locating multiple optima.
Multimodal optimization problems pose a great challenge of locating multiple optima simultaneously in the search space to the particle swarm optimization (PSO) community. In this paper, the motion principle of particles ...
A particle swarm optimization based memetic algorithm for dynamic optimization problems.
Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic. This paper investigates a particle swarm ...
Multi-population methods in unconstrained continuous dynamic environments: the challenges
The multi-population method has been widely used to solve unconstrained continuous dynamic optimization problems with the aim of maintaining multiple populations on different peaks to locate and track multiple changing ...
Particle swarm optimization with composite particles in dynamic environments.
In recent years, there has been a growing interest in the study of particle swarm optimization (PSO) in dynamic environments. This paper presents a new PSO model, called PSO with composite particles (PSO-CP), to address ...