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Particle swarm optimization (PSO) is a relatively new global optimization approach inspired by the social behavior of birds and fishes. Although this approach has proven to provide excellent convergence rates in different optimization problems, it has seldom been used in geophysical inversion. Here, we propose a PSO-based inversion strategy to jointly invert GPR and P-wave seismic traveltimes from co-located crosshole experiments. Using a synthetic data example, we demonstrate the potential of our approach. Comparing our results to the input models as well as to velocity models found by separately inverting the data using a standard linearized inversion approach, illustrates the benefits of using an efficient global optimization approach for such a joint inversion problem. These include a straightforward appraisal of uncertainty, non-uniqueness, and resolution issues as well as the possibility of an improved and more objective interpretation.