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Controlled Experimental Design for Statistical Comparison of Integer Programming Algorithms

Author

Listed:
  • Benjamin W. Lin

    (Rutgers University)

  • Ronald L. Rardin

    (Georgia Institute of Technology)

Abstract

Testing and comparison of integer programming algorithms is an integral part of the algorithm development process. When test problems are randomly generated, the techniques of statistical experimental design can provide a basis around which to structure computational experiments. This paper formulates the problem of constructing and analyzing controlled integer programming tests in the experimental design context and develops approaches to dealing with a number of issues that arise. Both analytic results and empirical evidence from a large experiment are employed in deriving the suggested techniques.

Suggested Citation

  • Benjamin W. Lin & Ronald L. Rardin, 1979. "Controlled Experimental Design for Statistical Comparison of Integer Programming Algorithms," Management Science, INFORMS, vol. 25(12), pages 1258-1271, December.
    • Handle: RePEc:inm:ormnsc:v:25:y:1979:i:12:p:1258-1271
    DOI: 10.1287/mnsc.25.12.1258
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    File URL: http://dx.doi.org/10.1287/mnsc.25.12.1258
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    Cited by:

    1. Miguel Lejeune & François Margot, 2011. "Optimization for simulation: LAD accelerator," Annals of Operations Research, Springer, vol. 188(1), pages 285-305, August.

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