Abstract
The particle swarm algorithm has shown ability to optimise in continuous problem spaces, although it can struggle in problem spaces containing multiple optima. A variant, called Waves of Swarm Particles (WoSP), has been shown to be able to handle problem spaces containing multiple optima by sequentially exploring these optima. In this chapter, the WoSP algorithm is adapted to suit complex quantised problem spaces and applied to a highly constrained problem with many constraint-violating solutions but few constraint-satisfying solutions. The performance obtained is remarkably good and reflects the power of the WoSP algorithm, which combines the search abilities of particle swarm with that of evolution.
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Hendtlass, T. (2009). Quantised Problem Spaces and the Particle Swarm Algorithm. In: Chiong, R., Dhakal, S. (eds) Natural Intelligence for Scheduling, Planning and Packing Problems. Studies in Computational Intelligence, vol 250. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04039-9_7
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DOI: https://doi.org/10.1007/978-3-642-04039-9_7
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