In order to solve complex optimization problems,the slime mold algorithm(SMA)has weak global search ability and is easy to fall into local optimal value.A multi-strategy fusion improved slime mold algorithm(TSMA)was proposed.Firstly,Logistic chaotic mapping was used to initialize the location of slime mold to increase the diversity of the population and improve the convergence speed of the algorithm.Then,the firefly algorithm(FA)was integrated to update the location formula based on fireflies's own brightness and attraction so as to increase the exploration and the population in the medium term.Finally,in the late iteration of the algorithm,the T distribution variation is introduced to mutate the optimal solution,so as to improve the ability of the popula-tion to jump out of the local optimal solution and improve the optimization accuracy.Through the test of 18 benchmark functions,and compared with other classical algorithms,the results show that TSMA is significantly better than other algorithms in the search process,thus verifying the effectiveness of the improved slime mold algorithm.
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