# Performance and Scalability of Particle Swarms with Dynamic and Partially Connected Grid Topologies

### Carlos M. Fernandes, Agostinho C. Rosa, Juan L. J. Laredo, Carlos Cotta, J. J. Merelo

#### Abstract

This paper investigates the performance and the scalability of dynamic and partially connected 2-dimensional topologies for Particle Swarms, using von Neumann and Moore neighborhoods. The particles are positioned on 2-dimensional grids of nodes, where they move randomly. The von Neumann or Moore neighborhood is used to decide which particles influence each individual. Structures with growing size are tested on a classical benchmark and compared to the lbest, gbest and the standard von Neumann and Moore configurations. The results show that the partially connected grids with von Neumann neighborhood structure perform more consistently than the other strategies, while the Moore partially connected structure performs similarly to the standard Moore configuration. Furthermore, the proposed structure scales similarly or better than the standard configuration when the problem size grows.

#### References

- Hseigh, S.-T., Sun, T.-Y, Liu, C.-C., Tsai, S.-J. 2009. Efficient Population Utilization Strategy for Particle Swarm Optimizers. IEEE Transactions on Systems, Man and Cybernetics-part B, 39(2), 444-456.
- Kennedy, J., Eberhart, R. 1995. Particle Swarm Optimization. In Proceedings of IEEE International Conference on Neural Networks, Vol.4, 1942-1948.
- Kennedy, J., Mendes, R., 2002. Population structure and particle swarm performance. In Proceedings of the IEEE World Congress on Evolutionary Computation, 1671-1676.
- Liang, J. J., Qin, A. K., Suganthan, P. N., Baskar, S., 2006. Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE Trans. Evolutionary Computation, 10(3), 281-296.
- Parsopoulos, K. E., Vrahatis, M. N., 2004. UPSO: A Unified Particle Swarm Optimization Scheme, Lecture Series on Computer and Computational Sciences, Vol. 1, Proceedings of the International Conference of "Computational Methods in Sciences and Engineering" (ICCMSE 2004), 868-87
- Parsopoulos, K. E., Vrahatis, M. N., 2005. Unified Particle Swarm Optimization in Dynamic Environments. Lecture Notes in Computer Science (LNCS), Vol. 3449, Springer, 590-599.
- T. Peram, K. Veeramachaneni, C. K. Mohan, Fitnessdistance-ratio based particle swarm optimization. In Proc. Swarm Intell. Symp., 2003, pp. 174-181.
- Shi, Y. Eberhart, R. C. 1998. A Modified Particle Swarm Optimizer. In Proceedings of IEEE 1998 International Conference on Evolutionary Computation, IEEE Press, 69-73.
- Trelea, I. C. 2003. The Particle Swarm Optimization Algorithm: Convergence Analysis and Parameter Selection. Information Processing Letters, 85, 317- 325.

#### Paper Citation

#### in Harvard Style

Fernandes C., C. Rosa A., L. J. Laredo J., Cotta C. and J. Merelo J. (2013). **Performance and Scalability of Particle Swarms with Dynamic and Partially Connected Grid Topologies** . In *Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2013)* ISBN 978-989-8565-77-8, pages 47-55. DOI: 10.5220/0004558600470055

#### in Bibtex Style

@conference{ecta13,

author={Carlos M. Fernandes and Agostinho C. Rosa and Juan L. J. Laredo and Carlos Cotta and J. J. Merelo},

title={Performance and Scalability of Particle Swarms with Dynamic and Partially Connected Grid Topologies},

booktitle={Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2013)},

year={2013},

pages={47-55},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0004558600470055},

isbn={978-989-8565-77-8},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2013)

TI - Performance and Scalability of Particle Swarms with Dynamic and Partially Connected Grid Topologies

SN - 978-989-8565-77-8

AU - Fernandes C.

AU - C. Rosa A.

AU - L. J. Laredo J.

AU - Cotta C.

AU - J. Merelo J.

PY - 2013

SP - 47

EP - 55

DO - 10.5220/0004558600470055