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A Hybridization of Sine Cosine Algorithm with Steady State Genetic Algorithm for Engineering Design Problems

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Book cover The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019) (AMLTA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 921))

Abstract

Sine Cosine Algorithm (SCA), a newly proposed optimization approach, has gained the interest of researchers to solve the optimization problems in different fields due to its efficiency and simplicity. As well as a genetic algorithm (GA) has proved its robustness in solving a large variety of complex optimization problems. In this paper, a hybridization of SCA with steady state genetic algorithm (SSGA) is proposed to solve engineering design problems. This approach integrates the merits of exploration capability of SCA and exploitation capability of SSGA to avoid exposure to early convergence, speed up the search process and quick the convergence to best results in a reasonable time. The proposed approach incorporates concepts from SSGA and SCA and generates individuals in a new generation by crossover and mutation operations of SSGA and also by mechanisms of SCA. Efficiency of the proposed algorithm is evaluated using two complex engineering design problems to verify its validity and reliability. Results show that the proposed approach has superior performance compared to other optimizations techniques.

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Author information

Authors and Affiliations

  1. Department of Mathematics, College of Science and Humanities Studies, Prince Sattam Bin Abdulaziz University, Al-Kharj, Kingdom of Saudi Arabia

    M. A. El-Shorbagy

  2. Department of Basic Engineering Science, Faculty of Engineering, Menoufia University, Shebin El-Kom, Egypt

    M. A. El-Shorbagy, M. A. Farag, A. A. Mousa & I. M. El-Desoky

  3. Mathematics and Statistics Department, Faculty of Science, Taif University, Taif, Kingdom of Saudi Arabia

    A. A. Mousa

Authors
  1. M. A. El-Shorbagy
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  2. M. A. Farag
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  3. A. A. Mousa
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  4. I. M. El-Desoky
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Corresponding author

Correspondence to M. A. Farag .

Editor information

Editors and Affiliations

  1. Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Faculty of Computers and Information, Benha University, Benha, Egypt

    Ahmad Taher Azar

  3. School of Computing, Science and Engineering, University of Salford, Salford, Greater Manchester, UK

    Tarek Gaber

  4. Department of Computer Science and Engineering, School of Computing and IT, Faculty of Engineering, Manipal University Jaipur, Jaipur, Rajasthan, India

    Roheet Bhatnagar

  5. Faculty of Computer and Information Science, Ain Shams University, Cairo, Egypt

    Mohamed F. Tolba

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El-Shorbagy, M.A., Farag, M.A., Mousa, A.A., El-Desoky, I.M. (2020). A Hybridization of Sine Cosine Algorithm with Steady State Genetic Algorithm for Engineering Design Problems. In: Hassanien, A., Azar, A., Gaber, T., Bhatnagar, R., F. Tolba, M. (eds) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2019). AMLTA 2019. Advances in Intelligent Systems and Computing, vol 921. Springer, Cham. https://doi.org/10.1007/978-3-030-14118-9_15

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