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

Understand

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.