Abstract
A random signal-based learning merged with simulated annealing (SARSL), which is serial algorithm, has been considered by the authors. But the serial nature of SARSL degrades its performance as the complexity of the search space is increasing. To solve this problem, this paper proposes a population structure of SARSL (PSARSL) which enables multi-point search. Moreover, adaptive partitioning method (APM) is used to reduce the optimization time. The validity of the proposed algorithm is conformed by applying it to a simple test function example and a general version of fuzzy controller design.
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References
De Jong, K.: An Analysis of the Behavior of a Class of Genetic Adaptive Systems. Ph.D. dissertation, Dept. Computer Sci., Univ. Michigan, Ann Arbor, MI (1975)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)
Han, C.W., Park, J.I.: Design of a Fuzzy Controller using Random Signal-based Learning Employing Simulated Annealing. In: Proc. of the IEEE Conference on Decision and Control, Sydney, Australia, pp. 396–397 (2000)
Kirkpatrick, S., Gelatt Jr., C.D., Vecchi, M.P.: Optimization by Simulated Annealing. Science 220(4598), 671–680 (1983)
Romeo, F., Sangiovanni-Vincentelli, A.: A Theoretical Framework for Simulated Annealing. Algorithmica 6, 302–345 (1991)
Sullivan, K.A., Jacobson, S.H.: A Convergence Analysis of Generalized Hill Climbing Algorithms. IEEE Trans. Automatic Control 46(8), 1288–1293 (2001)
Jeong, I.K., Lee, J.J.: Adaptive Simulated Annealing Genetic Algorithm for Control Applications. International Journal of Systems Science 27(2), 241–253 (1996)
Tang, Z.B.: Partitioned Random Search to Optimization. In: Proc. of the American Control Conference, San Francisco (1993)
Procyk, T.J., Mamdani, E.H.: A Linguistic Self-organizing Process Controller. Automatica 15(1), 15–30 (1979)
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Han, CW., Park, JI. (2006). Adaptive-Partitioning-Based Stochastic Optimization Algorithm and Its Application to Fuzzy Control Design. In: Antoniou, G., Potamias, G., Spyropoulos, C., Plexousakis, D. (eds) Advances in Artificial Intelligence. SETN 2006. Lecture Notes in Computer Science(), vol 3955. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11752912_9
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DOI: https://doi.org/10.1007/11752912_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34117-8
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