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Benchmarking nonlinear optimization software in technical computing environments

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  • János Pintér
  • Frank Kampas

Abstract

Our strategic objective is to develop a broadly categorized, expandable collection of test problems, to support the benchmarking of nonlinear optimization software packages in integrated technical computing environments (ITCEs). ITCEs—such as Maple, Mathematica, and MATLAB—support concise, modular and scalable model development: their built-in documentation and visualization features can be put to good use also in test model selection and analysis. ITCEs support the flexible inclusion of both new models and general-purpose solver engines for future studies. Within this broad context, in this article we review a collection of global optimization problems coded in Mathematica, and present illustrative and summarized numerical results obtained using the MathOptimizer Professional software package. Copyright Sociedad de Estadística e Investigación Operativa 2013

Suggested Citation

  • János Pintér & Frank Kampas, 2013. "Benchmarking nonlinear optimization software in technical computing environments," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(1), pages 133-162, April.
    • Handle: RePEc:spr:topjnl:v:21:y:2013:i:1:p:133-162
    DOI: 10.1007/s11750-011-0209-5
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    References listed on IDEAS

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    1. Castillo, Ignacio & Kampas, Frank J. & Pintér, János D., 2008. "Solving circle packing problems by global optimization: Numerical results and industrial applications," European Journal of Operational Research, Elsevier, vol. 191(3), pages 786-802, December.
    2. Jonathan P. K. Doye & Robert H. Leary & Marco Locatelli & Fabio Schoen, 2004. "Global Optimization of Morse Clusters by Potential Energy Transformations," INFORMS Journal on Computing, INFORMS, vol. 16(4), pages 371-379, November.
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