A levy flight based strategy to improve the exploitation capability of arithmetic optimization algorithm for engineering global optimization problems

Abstract

The existing arithmetic optimization algorithm is a meta-heuristics algorithm that utilizes distribution behaviors for the different parameters in mathematics. The different mathematical operator like division, subtraction, addition, and multiplication holds the inherent capability to explore global maxima and minima. In the proposed research, levy flight-based improved arithmetic optimization algorithm has been proposed for better optimal solutions to various engineering design problems. The fundamental arithmetic optimization algorithm's local search is slow and has a slow convergence rate due to its weak exploitation capacity. In the proposed work, the exploration and exploitation phase of the existing arithmetic optimization algorithm has been enhanced using the levy flight mechanism. In order to validate the effectiveness of the proposed optimizer, the improved algorithm has been tested for 23 standard benchmark problems and 10 real-life engineering design problems. The proposed algorithm has been compared with other classical algorithms like biogeography based optimization algorithm, arithmetic optimization algorithm, moth-flame optimization algorithm, genetic algorithm, flower pollination algorithm, particle swarm optimization, gray wolf optimization algorithm, BAT algorithm, chi-square algorithm, firefly algorithm, gravitational search algorithm, and differential evolution algorithm. The obtained result reveals that the proposed hybrid levy flight arithmetic optimization algorithm performs best on the number of test functions including engineering design problems with excellent fitness value and excellent convergence. This article is helpful to improve the exploitation capability of arithmetic optimization algorithms for engineering global optimization problems.

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