The Fortran subroutine NLPQLP solves smooth nonlinear programming problems by a sequential quadratic programming (SQP) algorithm. This version is specifically tuned to run under distributed systems controlled by an input parameter. In case of computational errors as for example caused by inaccurate function or gradient evaluations, a non-monotone line search is activated. Numerical results are included which show that in case of noisy function values, a significant improvement of the performance is achieved compared to the version with monotone line search. Further stabilization is obtained by performing internal restarts in case of errors when computing the search direction due to inaccurate derivatives. The new version of NLPQLP successfully solves more than 90 % of our 306 test examples subject to a stopping tolerance of 10^-7, although at most two digits in function values are correct and although numerical differentiation leads to additional truncation errors. In addition, automated initial and periodic scaling with restarts is implemented. The usage of the code is documented and illustrated by an example.

To download the report, click here: NLPQLP.pdf