A Multi-Strategy Improved Arithmetic Optimization Algorithm

Abstract

To improve the performance of the arithmetic optimization algorithm (AOA) and solve problems in the AOA, a novel improved AOA using a multi-strategy approach is proposed. Firstly, circle chaotic mapping is used to increase the diversity of the population. Secondly, a math optimizer accelerated (MOA) function optimized by means of a composite cycloid is proposed to improve the convergence speed of the algorithm. Meanwhile, the symmetry of the composite cycloid is used to balance the global search ability in the early and late iterations. Thirdly, an optimal mutation strategy combining the sparrow elite mutation approach and Cauchy disturbances is used to increase the ability of individuals to jump out of the local optimal. The Rastrigin function is selected as the reference test function to analyze the effectiveness of the improved strategy. Twenty benchmark test functions, algorithm time complexity, the Wilcoxon rank-sum test, and the CEC2019 test set are selected to test the overall performance of the improved algorithm, and the results are then compared with those of other algorithms. The test results show that the improved algorithm has obvious advantages in terms of both its global search ability and convergence speed. Finally, the improved algorithm is applied to an engineering example to further verify its practicability.

A Comprehensive Survey on Arithmetic Optimization Algorithm

“…Liu et al [102] presented an enhanced AOA, by employing a multi-strategy method to enhance the functionality of the AOA and address issues in the AOA. First, circle chaotic mapping is employed to broaden the population's diversity.…”

A Novel Enhanced Arithmetic Optimization Algorithm for Global Optimization

“…Pashaei et al introduced a hybrid binary AOA with a simulated annealing algorithm to solve the feature selection problem, the proposed algorithm obtained better classification accuracy and optimization results [20]. Liu et al proposed an improved AOA based on circle chaotic mapping, elite mutation approach and Cauchy disturbances to solve the function optimization and the engineering design problems, the optimization results of the proposed algorithm were better than those of other algorithms [21]. Khodadadi et al designed a dynamic AOA to solve the truss optimization problems, the proposed algorithm balanced exploration and exploitation to find the global solution in the search space [22].…”