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.
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McNabb, A., Seppi, K. (2012). The Apiary Topology: Emergent Behavior in Communities of Particle Swarms. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds) Parallel Problem Solving from Nature - PPSN XII. PPSN 2012. Lecture Notes in Computer Science, vol 7492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32964-7_17
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DOI: https://doi.org/10.1007/978-3-642-32964-7_17
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