"Assessing the Potential of Interior Methods for Nonlinear Optimization"
J.L. Morales, J.P. Goux, G. Liu, J. Nocedal, R. Waltz.
Lecture Notes in Computational Science and Engineering,
edited by L. T. Biegler, O. Ghattas, M. Heinkenschloss, B. van Bloemen
Vol. 30, pp. 167-183 Springer Verlag (2003).
A series of numerical experiments with interior point (LOQO, KNITRO) and active-set sequential quadratic programming (SNOPT, filterSQP) codes are reported and analyzed. The tests were performed with small, medium-size and moderately large problems, and are examined by problem classes. Detailed observations on the performance of the codes, and several suggestions on how to improve them are presented. Overall, interior methods appear to be strong competitors of active-set SQP methods, but all codes show much room for improvement.