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Ingeniería, investigación y tecnología

versión On-line ISSN 2594-0732versión impresa ISSN 1405-7743

Resumen

RIOS-WILLARS, Ernesto; LINAN-GARCIA, Ernesto; BATRES, Rafael  y  GARZA-GARCIA, Yolanda. Performance Profiles of the Algorithms Immune Network Algorithm and Bacterial Foraging Optimization Algorithm in Benchmark Functions. Ing. invest. y tecnol. [online]. 2016, vol.17, n.4, pp.479-490. ISSN 2594-0732.

This paper reports the application of the performance profiles model comparing the numerical methods Immune Network (AiNet) and Bacterial Foraging Optimization Algorithm (BFOA) in 18 benchmark optimization functions. Specifically robustness, efficiency and execution time of these methods were compared in search spaces with local minima multiple, bowl-shaped, plate-shaped, valley-shaped, steep ridges and other known optimization functions as styblinski-tang and beale function. The results show that the method AiNet (Castro et al., 2002) is more robust than the BFOA method (Passino, 2010) for the case studies considered in this work. However there are differences in the efficiency (number of evaluated functions and convergence time) between both methods. BFOA is the algorithm with best perform in terms of the number of evaluated functions.

Palabras llave : performance profile; benchmark functions; AiNet; BFOA; optimization.

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