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Evidence of Fundamental Difficulties in Nonlinear Optimization Code Comparisons

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Part of the book series: Lecture Notes in Economics and Mathematical Systems ((LNE,volume 199))

Abstract

Several nonlinear optimization code comparisons have been published, providing data for picking a code for a given application or developing new codes. The common performance measures (number of function evaluations, standardized computer time, number of problems solved) are intuitively machine independent, which encourages such use. Unfortunately, the relative performance of optimization codes does depend on the computer and compiler used for testing, and this dependence is evident regardless of the performance measure. In addition, relative performance measured on a single machine may depend significantly on the desired degree of accuracy, the choice of test problem(s), the chosen performance measure, and even the time of day (machine workload) when the tests are run. Numerical evidence of these difficulties is presented, based on tests of the same problem and algorithm decks on several different computers, with various compilers, problem sets, accuracy levels, and performance measures.

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© 1982 Springer-Verlag Berlin Heidelberg

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Eason, E.D. (1982). Evidence of Fundamental Difficulties in Nonlinear Optimization Code Comparisons. In: Mulvey, J.M. (eds) Evaluating Mathematical Programming Techniques. Lecture Notes in Economics and Mathematical Systems, vol 199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-95406-1_7

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  • DOI: https://doi.org/10.1007/978-3-642-95406-1_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-11495-6

  • Online ISBN: 978-3-642-95406-1

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