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The Apiary Topology: Emergent Behavior in Communities of Particle Swarms
Andrew McNabb and Kevin Seppi
Computer Science Department, Brigham Young University, USAa@cs.byu.edu
k@cs.byu.edu
Abstract. In the natural world there are many swarms in any geographical region. In contrast, Particle Swarm Optimization (PSO) is usually used with a single swarm of particles. We define a simple new topology called Apiary and show that parallel communities of swarms give rise to emergent behavior that is fundamentally different from the behavior of a single swarm of identical total size. Furthermore, we show that subswarms are essential for scaling parallel PSO to more processors with computationally inexpensive objective functions. Surprisingly, subswarms are also beneficial for scaling PSO to high dimensional problems, even in single processor environments.
Keywords: Particle Swarm Optimization, parallel PSO, swarm topology, subswarms, multiple swarms, parallel computation
LNCS 7492, p. 164 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2012