Transmission expansion planning has become a central challenge in the design of competitive electricity markets. The underlying optimization/decision problem exhibits a high level of complexity, being nonconvex, dynamic, and nonlinear, with multiple objective functions and a wide range of uncertainties. In this paper we propose a methodology for handling the expansion problem that involves a novel adaptation of an iterative optimization method based on response surface models already used successfully in the design and manufacture of integrated circuits. It is implemented in a distributed environment using Web services, and is validated and compared with a genetic algorithm based methodology. An application of the proposed methodology to the Chilean Central Interconnected System is then presented and analyzed. The results demonstrate its potential in the fields of risk analysis and decision support systems in power markets.