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In this work, we propose an efficient method for solving box constrainedderivative free optimization problems involving high dimensions. The proposedmethod relies on exploring the feasible region using a direct search approachbased on scaled conjugate gradient with quadratic interpolation models. Theextensive numerical computations carried out over test problems with varyingdimensions demonstrate the performance of the proposed method for derivativefree optimization.

A scaled conjugate gradient based direct search algorithm for high dimensional box constrained derivative free optimization