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Characterization of perturbed mathematical programs and interval analysis

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Abstract

Several authors have used interval arithmetic to deal with parametric or sensitivity analysis in mathematical programming problems. Several reported computational experiments have shown how interval arithmetic can provide such results. However, there has not been a characterization of the resulting solution interval in terms of the usual sensitivity analysis results. This paper presents a characterization of perturbed convex programs and the resulting solution intervals.

Interval arithmetic was developed as a mechanism for dealing with the inherent error associated with numerical computations using a computational device. Here it is used to describe error in the parameters. We show that, for convex programs, the resulting solution intervals can be characterized in terms of the usual sensitivity analysis results. It has been often reported in the literature that even well behaved convex problems can exhibit pathological behavior in the presence of data perturbations. This paper uses interval arithmetic to deal with such problems, and to characterize the behavior of the perturbed problem in the resulting interval. These results form the foundation for future computational studies using interval arithmetic to do nonlinear parametric analysis.

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References

  1. E. Adams and R. Lohner, “Error bounds and sensitivity analysis,” in: R. Stepleman et al. eds.,Scientific Computing (North-Holland, Amsterdam, 1983) pp. 213–222.

    Google Scholar 

  2. J. Dinkel and M. Tretter, “An interval arithmetic approach to sensitivity analysis in geometric programming,”Operations Research 35 (1987) 859–866.

    Google Scholar 

  3. J. Dinkel, M. Tretter and D. Wong, “Interval Newton methods and perturbed problems,”Applied Mathematics and Computation 28 (1988) 211–222.

    Google Scholar 

  4. A.V. Fiacco,Introduction to Sensitivity and Stability Analysis in Non-linear Programming (Academic Press, New York, 1983

    Google Scholar 

  5. E.R. Hansen, “Global optimization using interval analysis—The multi-dimensional case”,Numerische Mathematik 34 (1980) 247–270.

    Google Scholar 

  6. E.R. Hansen, “Global optimization with data perturbations,”Computers and Operations Research 11 (1984) 97–104.

    Google Scholar 

  7. L.J. Mancini and G.P. McCormick, “Bounding global minima,”Mathematics of Operations Research 1 (1976) 50–53.

    Google Scholar 

  8. L.J. Mancini and G.P. McCormick, “Bounding global minima with interval arithmetic,”Operations Research 27 (1979) 743–754.

    Google Scholar 

  9. R.E. Moore,Interval Analysis (Prentice-Hall, Englewood Cliffs, NJ, 1966).

    Google Scholar 

  10. R.E. Moore,Methods and Applications of Interval Analysis (SIAM, Philadelphia, PA, 1979).

    Google Scholar 

  11. H. Ratschek and J. Rokne,New Computer Methods for Global Optimization (Ellis Horwood, Chichester, UK, 1988).

    Google Scholar 

  12. S.M. Robinson, “Computable error bounds for nonlinear programming,”Mathematical Programming 5 (1973) 235–242.

    Google Scholar 

  13. S. Zlobec, “Characterizing an optimal input in perturbed convex programming,”Mathematical Programming 25 (1983) 109–121.

    Google Scholar 

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Dinkel, J.J., Tretter, M.J. Characterization of perturbed mathematical programs and interval analysis. Mathematical Programming 61, 377–384 (1993). https://doi.org/10.1007/BF01582158

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  • DOI: https://doi.org/10.1007/BF01582158

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