The effect of population density on the performance of a spatial social network algorithm for multi-objective optimisation

—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.

• Type: Conference
• Year: 2009
• Where: IPPS
• Authors: Andrew Lewis
• Keywords: Distributed And Parallel Computing, IPPS 2009, Social Network, Spatial Social Networks, —particle Swarm Optimisation