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The non-monopolize search (NO): a novel single-based local search optimization algorithm

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Abstract

Several optimization-based population search methods have been proposed; they use various operators that permit exploring the search space. These methods typically suffer from local search (LS) problems and are unbalanced between exploration and exploitation. Consequently, recent researchers sought to modify the algorithms to avoid search problems using local search techniques to intensify the exploitation when is necessary. This paper proposes a novel single-based local search optimization algorithm called the non-monopolize search (NO). The NO is a single-solution metaphor-free algorithm, and its operators are designed based to explore and exploit along the iterative process. The NO works only with a candidate solution, and the operators modify the dimension to move the current solution along the search space. The NO is an effective LS method that combines the benefits of exploration with exploitation. Different from other LS, the NO can escape from suboptimal solutions thanks to the randomness incorporated into its operators. This is the main advantage of the NO. Experiments are conducted on standard benchmark functions to validate the performance of the proposed non-monopolize search optimization technique. The results are compared with other well-known methods, and the proposed NO got better results. Moreover, the proposed NO can be considered a powerful alternative to improve the optimization algorithms’ performance and help avoid local search problems. Source codes of NO are publicly available at https://www.mathworks.com/matlabcentral/fileexchange/156154-the-non-monopolize-search-no.

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Data availability statement

Data are available from the authors upon reasonable request.

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Authors and Affiliations

  1. Computer Science Department, Prince Hussein Bin Abdullah Faculty for Information Technology, Al al-Bayt University, Mafraq, 25113, Jordan

    Laith Abualigah

  2. Center for Engineering Application and Technology Solutions, Ho Chi Minh City Open University, Ho Chi Minh City, Vietnam

    Thanh Cuong-Le

  3. College of Physics and Electronic Information Engineering, Zhejiang Normal University, Jinhua, 321004, China

    Mohammed A. A. Al-qaness

  4. Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, Egypt

    Mohamed Abd Elaziz

  5. Department of Computer, Damietta University, Damietta, 34517, Egypt

    Ahmed A. Ewees

  6. Departamento de Ingeniería Electro-Fotónica, Universidad de Guadalajara, CUCEI, Guadalajara, Jalisco, México

    Diego Oliva

  7. Zhejiang Optoelectronics Research Institute, Jinhua, 321004, China

    Mohammed A. A. Al-qaness

  8. Artificial Intelligence Research Center (AIRC), Ajman University, Ajman, 346, United Arab Emirates

    Mohamed Abd Elaziz

  9. Department of Electrical and Computer Engineering, Lebanese American University, Byblos, 13-5053, Lebanon

    Laith Abualigah & Mohamed Abd Elaziz

  10. MEU Research Unit, Middle East University, Amman, 11831, Jordan

    Laith Abualigah

  11. Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, 19328, Jordan

    Laith Abualigah

  12. Applied Science Research Center, Applied Science Private University, Amman, 11931, Jordan

    Laith Abualigah

  13. College of Engineering and Information Technology, Emirates International University, 16881, Sana’a, Yemen

    Mohammed A. A. Al-qaness

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  1. Laith Abualigah
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  2. Mohammed A. A. Al-qaness
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  3. Mohamed Abd Elaziz
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  4. Ahmed A. Ewees
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  5. Diego Oliva
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Correspondence to Laith Abualigah.

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Abualigah, L., Al-qaness, M.A.A., Abd Elaziz, M. et al. The non-monopolize search (NO): a novel single-based local search optimization algorithm. Neural Comput & Applic 36, 5305–5332 (2024). https://doi.org/10.1007/s00521-023-09120-9

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