Improving Performance of Evolutionary Algorithms with Application to Fuzzy Control of Truck Backer-Upper System

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

Mathematical Problems in Engineering, 2013, vol. 2013, 1-9

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.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:709027

DOI: 10.1155/2013/709027

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