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Improved multi-core arithmetic optimization algorithm-based ensemble mutation for multidisciplinary applications

Author

Listed:
  • Laith Abualigah

    (Amman Arab University
    Universiti Sains Malaysia)

  • Ali Diabat

    (New York University Abu Dhabi
    New York University)

Abstract

This paper proposes a new search method based on an augmented version of the Arithmetic Optimization Algorithm to solve various benchmark functions, engineering design cases, and feature selection problems. The proposed method is called MCAOA, combined with the Marine Predators Algorithm and a new proposed Ensemble Mutation Strategy. The Arithmetic Optimization Algorithm is a new meta-heuristic technique used to solve optimization problems. Sometimes, Arithmetic Optimization Algorithm faces convergence problems and falls into local optima for specific optimization problems, especially large-scale and multimodal problems. The Marine Predators Algorithm and Ensemble Mutation Strategy improve the Arithmetic Optimization Algorithm’s convergence rate and equilibrium in the exploration and exploitation search methods. The proposed method is tested on 23 different benchmark functions, seven common engineering design cases, and sixteen feature selection problems. The obtained results are compared with other well-known and state-of-the-art methods. The experimental results indicated that the proposed method found new best solutions for different complicated problems; the general performance is promising compared to other comparative methods.

Suggested Citation

  • Laith Abualigah & Ali Diabat, 2023. "Improved multi-core arithmetic optimization algorithm-based ensemble mutation for multidisciplinary applications," Journal of Intelligent Manufacturing, Springer, vol. 34(4), pages 1833-1874, April.
  • Handle: RePEc:spr:joinma:v:34:y:2023:i:4:d:10.1007_s10845-021-01877-x
    DOI: 10.1007/s10845-021-01877-x
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    References listed on IDEAS

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    1. Mohammed A. A. Al-qaness & Ahmed A. Ewees & Hong Fan & Laith Abualigah & Mohamed Abd Elaziz, 2020. "Marine Predators Algorithm for Forecasting Confirmed Cases of COVID-19 in Italy, USA, Iran and Korea," IJERPH, MDPI, vol. 17(10), pages 1-14, May.
    2. Xin Zhang & Dexuan Zou & Xin Shen, 2018. "A Novel Simple Particle Swarm Optimization Algorithm for Global Optimization," Mathematics, MDPI, vol. 6(12), pages 1-34, November.
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