Improving Performance of Evolutionary Algorithms with Application to Fuzzy Control of Truck Backer-Upper SystemReport as inadecuate




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Mathematical Problems in EngineeringVolume 2013 2013, Article ID 709027, 9 pages

Research Article

Iran University of Science and Technology, Tehran, Narmak 16846, Iran

Department of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, Norway

Young Researchers and Elites Club, Zarghan Branch, Islamic Azad University, Zarghan, Iran

Received 24 April 2013; Revised 22 September 2013; Accepted 22 September 2013

Academic Editor: Yang Xu

Copyright © 2013 Yousef Alipouri et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We propose a method to improve the performance of evolutionary algorithms EA. The proposed approach defines operators which can modify the performance of EA, including Levy distribution function as a strategy parameters adaptation, calculating mean point for finding proper region of breeding offspring, and shifting strategy parameters to change the sequence of these parameters. Thereafter, a set of benchmark cost functions is utilized to compare the results of the proposed method with some other well-known algorithms. It is shown that the speed and accuracy of EA are increased accordingly. Finally, this method is exploited to optimize fuzzy control of truck backer-upper system.





Author: Yousef Alipouri, Saeed Ahmadizadeh, Hamid Reza Karimi, S. Vahid Naghavi, and Ahad Soltani Sarvestani

Source: https://www.hindawi.com/



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