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Continuous Global Optimization in R

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  • Mullen, Katharine M.

Abstract

This article surveys currently available implementations in R for continuous global optimization problems. A new R package globalOptTests is presented that provides a set of standard test problems for continuous global optimization based on C functions by Ali, Khompatraporn, and Zabinsky (2005). 48 of the objective functions contained in the package are used in empirical comparison of' R implementations in terms of the quality of the solutions found and speed.

Suggested Citation

  • Mullen, Katharine M., 2014. "Continuous Global Optimization in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 60(i06).
    • Handle: RePEc:jss:jstsof:v:060:i06
    DOI: http://hdl.handle.net/10.18637/jss.v060.i06
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    References listed on IDEAS

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    1. Mullen, Katharine M. & Ardia, David & Gil, David L. & Windover, Donald & Cline, James, 2011. "DEoptim: An R Package for Global Optimization by Differential Evolution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i06).
    2. Gilli, Manfred & Maringer, Dietmar & Schumann, Enrico, 2011. "Numerical Methods and Optimization in Finance," Elsevier Monographs, Elsevier, edition 1, number 9780123756626.
    3. Mebane Jr., Walter R. & Sekhon, Jasjeet S., 2011. "Genetic Optimization Using Derivatives: The rgenoud Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i11).
    4. P. Kaelo & M. M. Ali, 2006. "Some Variants of the Controlled Random Search Algorithm for Global Optimization," Journal of Optimization Theory and Applications, Springer, vol. 130(2), pages 253-264, August.
    5. Ardia, David & Ospina, Juan & Giraldo, Giraldo, 2010. "Jump-Diffusion Calibration using Differential Evolution," MPRA Paper 26184, University Library of Munich, Germany, revised 25 Oct 2010.
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