Testing Unconstrained Optimization Software
Jorge J. Morè(Argonne National Laboratory), B. S. Garbow(Argonne National Laboratory), K. E. Hillstrom(Argonne National Laboratory)
Cited by 1,519Open Access
Abstract
Much of the testing of optimization software is inadequate because the number of test functmns is small or the starting points are close to the solution. In addition, there has been too much emphasm on measurmg the efficmncy of the software and not enough on testing reliability and robustness. To address this need, we have produced a relatwely large but easy-to-use collection of test functions and designed gmdelines for testing the reliability and robustness of unconstrained optimization software.
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