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1. Abstract Recently, a new way has been opened for the global optimization of a continuous function f: n → on a regular region S ≠ ∅ of n by characterizing the solutions as means of suitable random variables. This work presents a hybrid global optimization method of evolutionary type (ERPG-RF) involving random perturbations of descent methods in the mutation step and a Representation Formula of the global optimum for the generation of the initial population. The results show a good performance of the method, with emphasis of the influence of the Representation Formula on the performance, accelerating the search process, increasing the probability of success in tests and causing a considerable diminishing on the number of elements of the initial population. The numerical procedure is applied to the calibration of the spatial interaction models and compared to a classical method. The results show that the results are stable and the flexibility of the method makes that it can be easily used by professionals of the area.

A Procedure of Global Optimization and its Application to Estimate Parameters in Interaction Spatial Models