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Enhanced a hybrid moth-flame optimization algorithm using new selection schemes

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Abstract

This paper presents two levels of enhancing the basic Moth flame optimization (MFO) algorithm. The first step is hybridizing MFO and the local-based algorithm, hill climbing (HC), called MFOHC. The proposed algorithm takes the advantages of HC to speed up the searching, as well as enhancing the learning technique for finding the generation of candidate solutions of basic MFO. The second step is the addition of six popular selection schemes to improve the quality of the selected solution by giving a chance to solve with high fitness value to be chosen and increase the diversity. In both steps of enhancing, thirty benchmark functions and five IEEE CEC 2011 real-world problems are used to evaluate the performance of the proposed versions. In addition, well-known and recent meta-heuristic algorithms are applied to compare with the proposed versions. The experiment results illustrate that the proportional selection scheme with MFOHC, namely (PMFOHC) is outperforming the other proposed versions and algorithms in the literature.

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Notes

  1. The set of benchmark functions in our work is not matched totally with the other sets in the literature. Thus, we selected a group of benchmark function which matched with our work

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Authors and Affiliations

  1. Computer Science Department, Aqaba University of Technology, Aqaba, 77110, Jordan

    Mohammad Shehab

  2. Faculty of Science and Information Technology, Al-Zaytoonah University of Jordan, Amman, Jordan

    Hanadi Alshawabkah & Nagham AL-Madi

  3. Faculty of Computer Sciences and Informatics, Amman Arab University, Amman, Jordan

    Laith Abualigah

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  1. Mohammad Shehab
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  2. Hanadi Alshawabkah
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  3. Laith Abualigah
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  4. Nagham AL-Madi
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Correspondence to Mohammad Shehab.

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Shehab, M., Alshawabkah, H., Abualigah, L. et al. Enhanced a hybrid moth-flame optimization algorithm using new selection schemes. Engineering with Computers 37, 2931–2956 (2021). https://doi.org/10.1007/s00366-020-00971-7

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