Comparison between interval analysis and particle swarm optimization techniques for functions with restrictions
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Mar 16, 2011
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Abstract
This paper shows the comparison made between the particle swarm optimization (PSO) algorithm and the interval analysis optimization method for solving nonlinear-function optimization with equality and/or inequality constraints. The Interval analysis optimization method (IAO) was based on the one initially proposed by Ichida (1996). It was used to find the global optimum of a multimodal function with up to three variables, which is subject to equality and inequality constraints. It was found that the PSO algorithm was significantly faster for all functions, although its precision was limited. On the other hand, the IAO method was accurate in all cases, but took a considerably longer computational time.
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References
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HANSEN, E. Multidimensional Interval Newton Method. Reliable Computing. 2006, vol. 12, núm. 4, pp. 253-272.
HARGREAVES, G. I. Interval Analysis in MATLAB. Manchester: University of Manchester, 2002.
HORST, R. y PARDALOS, P. M. Handbook of Global Optimization. Journal of Applied Mathematics and Mechanics. 1995, Núm. 77, pp. 669-750.
ICHIDA, K. Constrained optimization using interval analysis. Computers and Industrial Engineering. 1996, vol. 31, núms. 3-4, pp. 933-937.
JANSSON, C. A global optimization method using interval arithmetic. Third International
IMACS-GAMM Symposium on Computer Arithmetic And Scientific Computing. Amsterdam, 1992.
KENNEDY, J. y EBERHART, R. Particle swarm optimization, Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ, 1995.
MIDENCE, D. y VARGAS, A. Estudio comparativo de algoritmos de computación evolutiva en la optimización de la confiabilidad en redes de distribución de potencia. Décimo tercer encuentro regional Iberoamericano de Cigre. Puerto Iguazú, Argentina, 2009.
MOORE, E.; R. KEARFOTT, R.; y CLOUD, M.J. Introduction to interval analysis. SIAM, Philadelphia, 2009. pp.105-127.
NEUMAIER, A. Introduction to numerical analysis. Cambridge, UK: Cambridge University Press, 2001.
RUMP, S. M. INTLAB–INTerval LABoratory. En: TiborCsende. Developments in Reliable Computing. Dordrecht: Kluwer Academic Publishers, 1999, pp. 77-104.
SAM. Another particle swarm toolbox [documento en línea]. 2009.
How to Cite
Vanegas-Ardila, D., Barragán-Niño, K. S., & Correa-Cely, R. (2011). Comparison between interval analysis and particle swarm optimization techniques for functions with restrictions. Ingenieria Y Universidad, 15(1), 47–60. https://doi.org/10.11144/Javeriana.iyu15-1.ctoa
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