Optimizing radial basis functions by d.c. programming and its use in direct search for global derivative-free optimization
In this paper, we address the global optimization of functions subject to bound and linear constraints without using derivatives of the objective function. We investigate the use of derivative-free models based on radial basis functions (RBFs) in the search step of direct-search methods of directional type. We also study the application of algorithms based on difference of convex (d.c.) functions programming to solve the resulting subproblems which consist of the minimization of the RBF models subject to simple bounds on the variables. Extensive numerical results are reported with a test set of bound and linearly constrained problems.
KeywordsGlobal optimization Derivative-free optimization Direct-search methods Search step Radial basis functions d.c. programming DCA
Mathematics Subject Classification (2000)90C26 90C30 90C56
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