A particle swarm optimizer with passive congregation.

By Shang He, Qing-Hua Wu, Jinyu Wen, Jon R. Saunders, R. Paton. Bio Systems, 2004

384 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Self-Adaptive Learning PSO-Based Deadline Constrained Task Scheduling for Hybrid IaaS Cloud (2014, background): “The particle flies toward a new position according to (13), and each value of the new position should not exceed the range of (13) At the beginning, the position and velocity of each particle in the swarm are initialized randomly.”
Size optimization of space trusses using Big Bang-Big Crunch algorithm (2009, methodology): “Example 4 is optimized using GA, PSO, a hybrid PSO (PSOPC [49]), BB–BC and the HBB–BC method.”
Particle swarm optimization algorithm: an overview (2017, background): “Moreover, in speed update equation, Hendtlass (2003) added memory ability to each particle and He et al. (2004) introduced passive congregation mechanism.”
Mathematical and Metaheuristic Applications in Design Optimization of Steel Frame Structures: An Extensive Review (2013, background): “In [181] particle swarm optimizer is improved by considering a passive congregation which is an important biological force preserving swarm integrity.”