With the successful application of swarm intelligence algorithms in the back analysis of pavement structural parameters, the problems of complex multivariate nonlinear optimization have been solved, while how to choose an appropriate algorithm is always being the urgent problem in the back analysis of pavement structural parameters. In view of the characteristics of back analysis of pavement structural parameters like complex models, numerous inversion parameters, and quite time-consuming forward calculation procedures, 8 common swarm intelligence algorithms are selected in the paper. Related researches on the performance of the algorithms under the limited number of forward calculation calls are carried out. In the paper, the group intelligence algorithm is further tested by taking as an example the inversion problem of the pavement structure parameters considering the material transverse isotropy and the contact state between layers. The research results show: ①Different algorithms have their own characteristics. Among them, particle swarm optimization (PSO), genetic algorithm (GA), brain storm optimization (BSO), artificial bee colony (ABC) and fireworks algorithm (FWA) work better in multi-peak problems. The firefly algorithm (FA) has a faster rate of convergence when solving the problem of a flat area near the optimal solution. For genetic algorithms (GA), the later rate of convergence of the real number coding method is higher than that of the binary coding method, but the search ability for multi-peak problems is weaker. Artificial fish-school algorithm (AFA) and shuffled frog leaping algorithm (SLA) have better optimization ability only under a larger number of forward calculation calls. ②For inversion of pavement structure parameters, PSO, GA, BSO and FA have good inversion results in deflection curve matching, while BSO can get the best inversion result in the view of correlation coefficient. Relevant research results can provide references for the selection of algorithms for complex back analysis problems in road engineering and other fields.