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An iterative scheme for the rigorous computation of electrically large problems is presented. The approach is based on a combination of the characteristic basis function method (CBFM) and the multilevel fast multipole algorithm (MLFMA) that can deal with very large problems that require an iterative solution process, even considering that the application of the CBFM entails an important reduction of the number of unknowns when compared to Method of Moments approaches based on subdomain functions. This reduction is due to the fact that the number of macro-basis functions, called characteristic basis functions (CBFs), is lesser than the number of low-level subsectional functions used to sample the geometry. In addition, the use of the MLFMA avoids the need to calculate and store the coupling terms in the reduced matrix that are not on or close to the diagonal, thereby optimizing the CPU time and the memory storage requirements. non-uniform rational B-splines (NURBS) surfaces are employed for the representation of the geometry and the CBFs are described in terms of curved rooftops generated in the parametric space. The associated macro-testing functions are defined as aggregations of curved razor-blade functions.