Acknowledgments Optimization of Non-Linear Gravity Numerical Examples

Conclusion

In summary, this computational method is based on a stochastic dynamics which enables, with probability one, the identification of a global minimum of the cost function, which depends on a continuous D-dimensional variable . While the number t of computational iterations increases, it mights happen that temporarily stabilizes on a given value, and eventually abandons it running towards the global minimum. >From the presented examples we conclude that the GSA shows a precise performance, although the computation time is rather expensive, a problem present in all global search methods. In several inverse problems in geophysics we have the non-linear case, where the standard gradient method are sometimes non effective as mentioned above. Since it is known the GSA is the fastest annealing approach we are stimulated to continue this research.