System Engineering and Productivity

System Engineering and Productivity

Comparison of the Efficiency of Metaheuristic Algorithms on Some Specific Functions with Adaptation of Fuzzy Parameters

Document Type : Research Paper

Authors
1 Corresponding author: Assistant Professor, Department of Industrial Engineering, Faculty of Industrial Engineering, University of Eyvanekey, Eyvanekey, Iran
2 M.Sc., Department of Computer Engineering, Faculty of Electrical, Computer and Mechanical Engineering, University of Eyvanekey, Eyvanekey, Iran
Abstract
In this study, the performance of metaheuristic algorithms (PSO4 and ICA5) on some specific functions has been compared by adapting fuzzy parameters. These fuzzy algorithms, by considering each of these test functions as an objective or fitness function, do their job, which is to reach the global minimum of each of these test functions. Considering the uncertainty in this study, a more realistic modeling of the problem was created so that the solutions generated from this model have greater ability to be implemented. In this study, we have improved the convergence speed to the global minimum of each of these functions and used two methods, PSO and ICA with fuzzy parameters, which, in addition to reducing the computational time and increasing the convergence speed, a comparison was also made between the performance of fuzzy PSO and fuzzy ICA. We concluded that the fuzzy ICA algorithm has a faster convergence speed than the fuzzy PSO algorithm.
Keywords

Copyright ©, Hossein Eghbali, Samaneh Asghari Kenarsari

 

License

This article is released under the Creative Commons Attribution (CC BY 4.0) license. Anyone is free to copy, share, translate, and adapt this article for any purpose, whether commercial or non-commercial, as long as proper citation is given to the authors and original publication.

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