Swarm intelligence is an important and popular branch of computational intelligence. This technique is based on the analysis of the collective behaviour of swarms in nature and of social phenomena, and it is aimed to solve highly non-linear problems. The optimization performances of these techniques are highly affected by the specific choice of the working parameters. In this chapter, the modelling of interaction in swarm intelligence is done by means of different models, and the space of the working parameter is finally divided accordingly to the specific dynamic behaviour of the swarm for each point of this space. In this analysis, the attention has been focused in two optimization algorithms: the well-known particle swarm optimization and the recently developed social network optimization.

Modelling of interaction in swarm intelligence focused on particle swarm optimization and social networks optimization

Niccolai, A;Grimaccia, F;Mussetta, M;Zich, RE
2018

Abstract

Swarm intelligence is an important and popular branch of computational intelligence. This technique is based on the analysis of the collective behaviour of swarms in nature and of social phenomena, and it is aimed to solve highly non-linear problems. The optimization performances of these techniques are highly affected by the specific choice of the working parameters. In this chapter, the modelling of interaction in swarm intelligence is done by means of different models, and the space of the working parameter is finally divided accordingly to the specific dynamic behaviour of the swarm for each point of this space. In this analysis, the attention has been focused in two optimization algorithms: the well-known particle swarm optimization and the recently developed social network optimization.
SWARM INTELLIGENCE, VOL 1: PRINCIPLES, CURRENT ALGORITHMS AND METHODS
978-1-78561-628-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1128159
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