Abstract: In order to solve a series of problems of zebra optimization algorithm,such as easy to fall into local optimization and slow convergence,this paper proposes a multi-strategy fusion improved zebra optimization algorithm(MSI-ZOA).Firstly,the random sequence generated by Tent chaotic map is used to initialize the population,which improves the distribution quality of the initialized population in the search space and strengthens the global exploration ability.Secondly,taking advantage of the heavy-tailed property of Levi's flight,the search space coverage is increased,and the global exploration ability in the foraging stage of zebra optimization algorithmZOA) is strengthened.Nextly,using a sine and cosine optimization algorithm with hyperbolic cosine enhancement factor,it can effectively pick out the local optimal solution and improve the convergence speed when it is applied to the predator-resistant stage of ZOA algorithm.Finally,the MSI-ZOA algorithm,ZOA algorithm,vulture optimization algorithm(AVOA),artificial hummingbird algorithm(AHA),gorilla troop optimization algorithm(GTO),arithmetic optimization algorithm(AOA) and northern goshawk optimization algorithm(NGO) are tested on eight benchmark functions,and the results show that MSI-ZOA algorithm is superior to the other six algorithms in convergence speed and global search.

Key words: Zebra optimization algorithm, Tent chaotic mapping, Levi flight, Hyperbolic cosine enhancement factor, Sine cosine optimization algorithm