Multi-Objective Particle swarm optimization of vertical electrical sounding and time-domain electromagnetic data

This work presents the use of the Multi-Objective version of the Particle Swarm Optimization algorithm to simultaneously optimize different geophysical data sets. The method was applied to two field data sets of Vertical Electrical Sounding and Time-Domain Electromagnetic data, thus dealing with the minimization of two objective functions. The exploration and exploitation of the parameter search space were balanced by iteratively changing the key coefficients of the algorithm: the inertia weight, the accelerations and mutation operator. The best solution was selected by applying the concept of Pareto optimality to the two objectives. The Occam-like approach was successful in yielding a smooth resistivity model, highly comparable to the results of previous research.