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A scaled conjugate gradient based direct search algorithm for high dimensional box constrained derivative free optimization
In this work, we propose an efficient method for solving box constrained
derivative free optimization problems involving high dimensions. The proposed
method relies on exploring the feasible region using a direct search approach
based on scaled conjugate gradient with quadratic interpolation models. The
extensive numerical computations carried out over test problems with varying
dimensions demonstrate the performance of the proposed method for derivative
free optimization.Comment: 24 pages, 5 figures, 6 table