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Hybrid Optimization Algorithm Based on Arithmetic and Golden Sine Algorithms for Constrained Engineering Problem

Qingxin Liu,H. Jia,Di Wu,Q. Qi,Xiaoqin Huang

Published 2022 in ACM Cloud and Autonomic Computing Conference

ABSTRACT

Arithmetic Optimization Algorithm (AOA) is a newly proposed meta-heuristics (MAs) inspired by the major arithmetic operators. Although it provides satisfactory solutions to several real-world problems, when facing complex problems, AOA also easily suck into local optimal solution and slow convergence speed. Golden Sine Algorithm (Gold-SA) is another MAs and has an acceptable local search capability with fewer parameters. Considering these situations, this paper we propose a novel hybrid optimization algorithm (HAGA) that integrated both AOA and Gold-SA to achieve superior optimization ability. In HAGA, the search agents are divided into two consistent subgroups and optimized by AOA and Gold-SA, respectively. By this operator, we can exchange useful information and utilize their advantages to find the optimal or near-optimal regions throughout the iterative process. In addition, Lens Opposition- Based Learning (LOBL) is employed to accelerate the convergence speed. We test the proposed method using thirteen benchmark functions and a constrained engineering problem. The results prove the significant superiority of HAGA to those of four counterpart methods in terms of optimization accuracy and convergence speed.

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