Optimality Measures for Performance Profiles

We examine the importance of optimality measures when benchmarking a set of solvers, and show that scaling requirements lead to a convergence test for nonlinearly constrained optimization solvers that uses a mixture of absolute and relative error measures. We demonstrate that this convergence test is well behaved at any point where the constraints satisfy the Mangasarian-Fromovitz constraint qualification and also avoids the explicit use of a complementarity measure. Computational experiments explore the impact of this convergence test on the benchmarking process with performance profiles.


Preprint ANL/MCS-P1155-0504, Argonne National Laboratory, 05/04



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