A modified mnemonic enhancement optimization method for solving parametric nonlinear programming problems

A mnemonic enhancement optimization framework based on radial basis function (RBF-MEO), which is concerned with the application of RBF interpolation for generation of starting points in parametric nonlinear optimization, is studied in this work. Some theories of interior point algorithm support that the RBF-MEO method is very suitable for collaborating with interior point solvers, such as IPOPT. Numerical experiments illustrate that good accuracy and high rate of convergence are obtained by IPOPT with RBF-MEO.