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Digital Library of the
European Council for Modelling and Simulation |
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Title: |
Optimisation Of Boids Swarm Model Based On Genetic Algorithm And Particle
Swarm Optimisation Algorithm (Comparative Study) |
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Authors: |
Saleh Alaliyat, Harald Yndestad, Filippo Sanfilippo |
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Published in:
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(2014).ECMS 2014 Proceedings edited
by: Flaminio Squazzoni,
Fabio Baronio, Claudia Archetti,
Marco Castellani European Council for
Modeling and Simulation. doi:10.7148/2014 ISBN:
978-0-9564944-8-1 28th
European Conference on Modelling and Simulation, Brescia,
Italy, May 27th – 30th,
2014 |
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Citation
format: |
Saleh Alaliyat, Harald Yndestad, Filippo Sanfilippo (2014). Optimisation Of Boids Swarm Model Based On Genetic Algorithm And Particle
Swarm Optimisation Algorithm (Comparative Study), ECMS
2014 Proceedings edited by: Flaminio Squazzoni, Fabio Baronio,
Claudia Archetti, Marco Castellani European
Council for Modeling and Simulation. doi:10.7148/2014-0643 |
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DOI: |
http://dx.doi.org/10.7148/2014-0643 |
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Abstract: |
In this paper, we present
two optimisation methods for a generic boids swarm model which is
derived from the original Reynolds’ boids model to
simulate the aggregate moving of a fish school. The aggregate motion is the
result of the interaction of the relatively simple behaviours
of the individual simulated boids1. The aggregate moving vector is a linear
combination of every simple behaviour rule vector.
The moving vector coefficients should be identified and optimised
to have a realistic flocking moving behaviour. We
proposed two methods to optimise these
coefficients, by using genetic algorithm (GA) and particle swarm optimisation algorithm (PSO). Both GA and PSO are
population based heuristic search techniques which
can be used to solve the optimisation problems. The
experimental results show that optimisation of boids model by using PSO is faster and gives better
convergence than using GA. |
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