Hybrid Algorithm of Sparrow Algorithm and Arithmetic Optimization Algorithm Based on Hamiltonian Graph

Abstract

Aiming at the shortcomings of sparrow search algorithm (SSA), such as decreased population diversity in the late iteration and easily falling into local optimal solution, a hybrid algorithm of sparrow search algorithm and arithmetic optimization algorithm based on Hamiltonian graph (HSSAAOAH) is proposed. Firstly, the multiplica-tion and division operator of arithmetic optimization algorithm (AOA) is introduced into the discoverer-follower model and reconnaissance mechanism of SSA. The high distribution of multiplication and division operator is used to improve the randomness of later optimization. Secondly, the population composed by all the individuals is transferred into an undirected weight graph. After each iteration, a Hamiltonian cycle and its length composed of individuals will be computed according to a modified cycle algorithm, and the population optimization trend is measured by the ratio of the Hamiltonian cycle length. Then, for the progeny that fails to perform effective convergence, a certain number of individuals are randomly generated to replace the last ones according to the greedy algorithm, which improves the quality of solution and enhances the ability to jump out of local extrema. Finally, HSSAAOAH and different optimization algorithms are simulated on the benchmark function and two engineering design problems. The results show that HSSAAOAH algorithm has faster convergence speed, higher optimization accuracy, and good robustness and optimization performance.

Keywords

• sparrow search algorithm (ssa); arithmetic optimization algorithm (aoa); hamiltonian graph; modified cycle algorithm