Application Research Of Grasshopper Optimization Algorithm

Grasshopper optimization algorithm(GOA)and its application research is to simulate natural grasshopper populations feeding behavior and put forward an intelligent optimization algorithm,which make use of the social forces between the grasshoppers draw the space is divided into space,comfortable space and exclusive space,according to the variation of different distance between grasshopper size to change space to find the optimal location.The algorithm is characterized by simple structure,strong stability,few parameters and fast convergence.However,with the development of the research,the researchers found that the algorithm's population diversity and convergence accuracy need to be improved.Therefore,the thesis improves the locust optimization algorithm and applies the improved locust optimization algorithm to practical problems.The thesis mainly completes the following three aspects of research work:(1)The grasshopper optimization algorithm based on the neighborhood centriod was proposed,and the neighborhood centriod strategy was added to the grasshopper optimization algorithm.In the neighborhood center of gravity of locusts optimization algorithm,the population is divided into several different neighborhood,direct interaction between individual locusts,find a local neighborhood point of reference for the center of gravity to calculate the center of gravity position,as a new individual reverse points to facilitate the full use of group search experience while maintaining the diversity of population,enhance the detection algorithm.(2)The grasshopper optimization algorithm based on the based on chaos is proposed,ten different chaotic strategy to join the grasshopper optimization algorithm respectively,the strategy is mainly used to increase the diversity of population,improve the convergence speed in the late of the algorithm,compared with the original algorithm,the experimental results show that introducing chaos strategies to improvethe precision and convergence speed of the algorithm.(3)The TSP problem is a classical NP-hard problem.The grasshopper optimization algorithm is used to solve the spherical traveling salesman problem.Experimental results show that the grasshopper optimization algorithm can obtain a better path scheme.