Photoelectron diffraction (PED) is an experimental technique widely used to performstructural determinations of solid surfaces. Similarly to low-energy electron diffraction(LEED), structural determination by PED requires a fitting procedure between theexperimental intensities and theoretical results obtained through simulations. Multiplescattering has been shown to be an effective approach for making such simulations. Thequality of the fit can be quantified through the so-called R-factor. Therefore, the fittingprocedure is, indeed, an R-factor minimization problem. However, the topography of theR-factor as a function of the structural and non-structural surface parameters to bedetermined is complex, and the task of finding the global minimum becomes tough,particularly for complex structures in which many parameters have to be adjusted. In thiswork we investigate the applicability of the genetic algorithm (GA) global optimizationmethod to this problem. The GA is based on the evolution of species, and makes use ofconcepts such as crossover, elitism and mutation to perform the search. We showresults of its application in the structural determination of three different systems:the Cu(111) surface through the use of energy-scanned experimental curves; theAg(110)–c(2 × 2)-Sb system, in which a theory–theory fit was performed; and the Ag(111) surface for whichangle-scanned experimental curves were used. We conclude that the GA is a highly efficientmethod to search for global minima in the optimization of the parameters that best fitthe experimental photoelectron diffraction intensities to the theoretical ones.