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Testing Unconstrained Optimization Software

Testing Unconstrained Optimization Software Testing Unconstrained Optimization Software JORGE J. MORI~, BURTON S. GARBOW, and KENNETH E. HILLSTROM Argonne National Laboratory 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. Key Words and Phrases: performance testing, systems of nonlinear equatmns, nonlinearleast squares, unconstrained minnmzation, optimizatmn software CR Categorms. 4.6, 5.15, 5.41 The Algorithm: FORTRAN Subroutines for Testing Unconstrained Optimizatmn Software. ACM Trans. Math. Software 7, 1 (March 1981), 136-140. 1. INTRODUCTION When an algorithm is presented in the optimization literature, it has usually been tested on a set of functions. The purpose of this testing is to show that the algorithm works and, indeed, that it works better than other algorithms in the same problem area. In our opinion these claims are usually unwarranted because it is often the case that there are http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Mathematical Software (TOMS) Association for Computing Machinery

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References (24)

Publisher
Association for Computing Machinery
Copyright
Copyright © 1981 by ACM Inc.
ISSN
0098-3500
DOI
10.1145/355934.355936
Publisher site
See Article on Publisher Site

Abstract

Testing Unconstrained Optimization Software JORGE J. MORI~, BURTON S. GARBOW, and KENNETH E. HILLSTROM Argonne National Laboratory 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. Key Words and Phrases: performance testing, systems of nonlinear equatmns, nonlinearleast squares, unconstrained minnmzation, optimizatmn software CR Categorms. 4.6, 5.15, 5.41 The Algorithm: FORTRAN Subroutines for Testing Unconstrained Optimizatmn Software. ACM Trans. Math. Software 7, 1 (March 1981), 136-140. 1. INTRODUCTION When an algorithm is presented in the optimization literature, it has usually been tested on a set of functions. The purpose of this testing is to show that the algorithm works and, indeed, that it works better than other algorithms in the same problem area. In our opinion these claims are usually unwarranted because it is often the case that there are

Journal

ACM Transactions on Mathematical Software (TOMS)Association for Computing Machinery

Published: Mar 1, 1981

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