Application Research Of Whale Optimization Algorithm

Whale Optimization Algorithm(WOA)is a novel swarm intelligence technique which simulated the bubble-net hunting stragegy of humpback whales in the ocean.It has simple structure,fewer parameters and powerful search ability,furthermore,it is quite easy to implement.However,the previous studies of WOA are still in the early period and the WOA still has demerits with regard to low precision,slow convergence and easily get trapped into local optimum.In this paper,the shortcomings of WOA are deeply analysis and improved.This paper proposed 3 different variants of WOA,in the same time,the new variants of WOA are applied to some practical optimization problems which aiming to consolidate the theoretical basis of WOA and expand the range of application.The main contributions of this paper are as follows:(1)In order to enhance the global search ability of the basic WOA then smooth balance its exploration and exploitation ability to reach higher accuracy,Lévy flight trajectory is studied.A lévy flight trajectory-based whale optimization algorithm(LWOA)is proposed with using lévy flight trajectory helps to improve the global search ability of WOA.LWOA is used to solve 23 classical benchmarkfunctions and 5 standard engineering applications and compare with different algorithms.The experiments results showed that the performances of LWOA are superior.(2)In order to accelerate the convergence rate of WOA,the basic principle of ranking-based mutation operator is introduced.A ranking-based whale optimization algorithm(RWOA)is proposed.The ranking-based mutation operator is integrated into the basic WOA where whale individuals updated positions with using ranking-based mutation operator first then using its own mechanism during the optimization process for the purpose to speed up the convergence rate.In addition,RWOA is applied to 3 different IIR system identifications with different orders,the simulation results showed the efficiency and stability of RWOA.(3)In order to improve the local search ability of WOA,the local search strategy from flower pollination algorithm is studied.A local search strategy –based whale optimization algorithm(IWOA)is proposed,the local search strategy is introduced into the local phase of WOA to improve its exploition capability.In the same time,the hybrid model of IWOA with atomic potential matching(APM)is applied to shape matching problems.The experimental results of 3 different shape macthings show IWOA algorithm based on APM model can match successfully and the similarity is high.