Hybrid Particle Swarm and Ant Colony Optimization for Surface Wave Analysis

Inversion of surface wave dispersion curves is challenging for most local-search methods due to its high nonlinearity and to its multimodality. In this study, we implemented and tested a surface wave dispersion curve inversion scheme based on PSO ACO (Particle Swarm Optimization hybridized with Ant Colony Optimization) to overcome its slow convergence and to avoid its wandering neighborhood the global minimum in the final stage of search. The proposed inverse procedure was applied to nonlinear inversion of fundamental-mode surface wave dispersion curves for near-surface shear (S)-wave velocities. The calculation efficiency and stability of the proposed scheme are tested on a five-layer synthetic model and a real example. Results from both synthetic and actual field data demonstrate that PSOACO algorithm applied to surface wave analysis should be considered good not only in terms of accuracy but also in terms of computation effort.