Practical evaluation of an interior point three-D filter line search method using engineering design problems

We present a primal-dual interior point method for nonlinear optimization that relies on a line search filter strategy to allow convergence from poor starting points. The filter technique has already been adapted to interior point methods in different ways. Our filter relies on three components. Each entry in the filter includes the feasibility measure, the centrality measure and the barrier objective function value as the optimality measure. Numerical experiments carried out with a set of engineering design problems show that our filter approach is effective in reaching the solution. A comparison with other well-known methods is also reported