Aiming at the problems of early convergence and insufficient global optimization ability of sparrow search algorithm when solving complex problems,an improved sparrow search algorithm(ISSA)was proposed.Firstly,the individual direction information and population direction information were introduced to update the follower's location and improve the global search ability of the algorithm.Secondly,the number of watchmen was dynamically adjusted to expand the search range of sparrows,and the binary tournament selection strategy was used to select individual watchmen to increase the diversity of sparrow population.Finally,a fixed perturbation term is added to provide an opportunity to escape the local optimal.In the CEC2013 test set,ISSA and other five optimization algorithms were simulated in the same dimension,and the Friedman test and Wilcoxon rank sum test of each algorithm were compared.The comparison results showed that ISSA had significant advantages in convergence performance and stability,and was suitable for solving complex problems.
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