The Effect of Population Density on the Performance of a Spatial Social Network Algorithm for Multi-objective Optimisation
Abstract
Particle Swarm Optimisation (PSO) is increasingly being applied to optimisation of multi-objective problems in engineering design and scientific investigation. This paper investigates the behaviour of a novel algorithm based on an extension of the concepts of spatial social networks using a model of the behaviour of locusts and crickets. In particular, observation of locust swarms suggests a specific dependence on population density for ordered behaviour. Computational experiments demonstrate that both the new, spatial, social network algorithm and a conventional MOPSO algorithm exhibit improved performance with increased swarm size and crowding. This observation may have particular significance for design of some forms of distributed PSO algorithms.
Conference Title
Conference Proceedings: IEEE International Symposium on Parallel & Distributed Processing
Copyright Statement
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Subject
Optimisation