Skip to main content
Log in

Global multi-parametric optimal value bounds and solution estimates for separable parametric programs

  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

In this tutorial, a strategy is described for calculating parametric piecewise-linear optimal value bounds for nonconvex separable programs containing several parameters restricted to a specified convex set. The methodology is based on first fixing the value of the parameters, then constructing sequences of underestimating and overestimating convex programs whose optimal values respectively increase or decrease to the global optimal value of the original problem. Existing procedures are used for calculating parametric lower bounds on the optimal value of each underestimating problem and parametric upper bounds on the optimal value of each overestimating problem in the sequence, over the given set of parameters. Appropriate updating of the bounds leads to a nondecreasing sequence of lower bounds and a nonincreasing sequence of upper bounds, on the optimal value of the original problem, continuing until the bounds satisfy a specified tolerance at the value of the parameter that was fixed at the outset. If the bounds are also sufficiently tight over the entire set of parameters, according to criteria specified by the user, then the calculation is complete. Otherwise, another parameter value is selected and the procedure is repeated, until the specified criteria are satisfied over the entire set of parameters. A parametric piecewise-linear solution vector approximation is also obtained. Results are expected in the theory, computations, and practical applications. The general idea of developing results for general problems that are limits of results that hold for a sequence of well-behaved (e.g., convex) problems should be quite fruitful.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. H.P. Benson, Algorithms for parametric nonconvex programming, J. Optim. Theory Appl. 38 (1982) 319–340.

    Google Scholar 

  2. J.W. Daniel, Stability of the solution of definite quadratic programs, Math. Programming 5(1) (1973) 41–53.

    Google Scholar 

  3. J.J. Dinkel, G.A. Kochenberger and S.N. Wong, Sensitivity analysis procedures for geometric programs: Computational aspects, ACM Trans. Math. Software 4(1) (1978) 1–14.

    Google Scholar 

  4. J.J. Dinkel, G.A. Kochenberger and S.N. Wong, Parametric analysis in geometric programming: An incremental approach, in:Mathematical Programming with Data Perturbations I, A.V. Fiacco (ed.), Lecture Notes in Pure and Applied Mathematics, Vol. 73 (Marcel Dekker, New York, 1982) pp. 93–109.

    Google Scholar 

  5. A.V. Fiacco, Computable optimal value bounds and solution vector estimates for general parametric NLP programs, Technical Paper Serial T-451, Institute for Management Science and Engineering (IMSE), George Washington University (GWU) (1981).

  6. A.V. Fiacco,Introduction to Sensitivity and Stability Analysis in Nonlinear Programming (Academic Press, New York, 1983).

    Google Scholar 

  7. A.V. Fiacco and F.A. Amodeo, Solution and sensitivity analysis of RESDYN Model 1A using SENSUMT, Technical Paper Serial T-485/84, IMSE, GWU (1984).

  8. A.V. Fiacco and A. Ghaemi, A user's manual for SENSUMT: A penalty function computer program for solution, sensitivity analysis and optimal value bound calculation in parametric nonlinear programs, Technical Paper Serial T-434, IMSE, GWU (1980).

  9. A.V. Fiacco and A. Ghaemi, A closed form local solution of a nonlinear structural design problem in terms of design parameters, Technical Paper Serial T-449, IMSE, GWU (1981).

  10. A.V. Fiacco and A. Ghaemi, Sensitivity and parametric bound analysis of optimal steam turbine exhaust annulus and condenser sizes, Technical Paper Serial T-437, IMSE, GWU (1981).

  11. A.V. Fiacco and A. Ghaemi, Sensitivity analysis of a nonlinear structural design problem, Comput. Oper. Res. 9 (1982) 29–55.

    Google Scholar 

  12. A.V. Fiacco and A. Ghaemi, Sensitivity analysis of a nonlinear water pollution control model using an upper Hudson River data base, Oper. Res. 30 (1982) 1–28.

    Google Scholar 

  13. A.V. Fiacco and J. Kyparisis, Computable parametric bounds for simultaneous large perturbations of thirty parameters in a water pollution abatement GP model, Part I: Optimal value bounds, Technical Paper Serial T-453, IMSE, GWU (1981).

  14. A.V. Fiacco and J. Kyparisis, Computable parametric bounds for simultaneous large perturbations of thirty parameters in a water pollution abatement GP model. Part II: Refinement of optimal value bounds and parametric solution bounds, Technical Paper Serial T-461, IMSE, GWU (1981).

  15. A.V. Fiacco and J. Kyparisis, Convexity and concavity properties of the optimal value function in parametric nonlinear programming, J. Optim. Theory Appl. 48 (1986) 95–126.

    Google Scholar 

  16. A.V. Fiacco and S.M. Yacout, Sensitivity analysis and parametric optimal value bounds for a nonconvex programming model: International intra-company transfer pricing, Preprint, GWU (1986).

  17. A.V. Fiacco and S.M. Yacout, Parametric analysis of a portfolio selection problem, Preprint, GWU (1986).

  18. A. Ghaemi, Computable stability analysis techniques fr nonlinear programming: Sensitivities, optimal value bounds, and applications, Ph.D. dissertation, School of Engineering and Applied Science, George Washington Univ. Washington, DC (1980).

    Google Scholar 

  19. J. Kyparisis, Sensitivity analysis in posynomial geometric programming, J. Optim. Theory Appl. 57 (1988) 85–121.

    Google Scholar 

  20. J. Kyparisis and A.V. Fiacco, Generalized convexity and concavity properties of the optimal value function in parametric nonlinear programming, Math. Programming 39 (1987) 285–304.

    Google Scholar 

  21. O.L. Mangasarian and J.B. Rosen, Inequalities for stochastic nonlinear programming problems, Oper. Res. 12 (1964) 143–154.

    Google Scholar 

  22. G.P. McCormick, Computability of global solutions to factorable nonconvex programs, Part I: Convex underestimating problems, Math. Programming 10(2) (1976) 147–175.

    Google Scholar 

  23. G.P. McCormick,Nonlinear Programming: Theory, Algorithms, and Applications (Wiley, 1983).

  24. S.M. Robinson, Generalized equations and their solutions, Part I: Basic theory, in:Mathematical Programming Studies, Vol. 10, P. Huard (ed.) (North-Holland, Amsterdam, 1979) pp. 128–141.

    Google Scholar 

  25. S.M. Robinson, Strongly regular generalized equations, Math. Oper. Res. 5 (1980) 43–62.

    Google Scholar 

  26. S.M. Robinson, Generalized equations and their solutions, Part II: Applications to nonlinear programming, MRC Technical Summary Report No. 2048, Mathematics Research Center, University of Wisconsin, Madison (1980).

    Google Scholar 

  27. L.S. Thakur, Solving highly nonlinear convex separable programs using successive approximation, in:Applications of Stability Analysis in Optimization, A.V. Fiacco (ed.), Vol. 11, no. 2 (Pergamon, New York, 1984) pp. 113–128.

    Google Scholar 

  28. S. Yacout, Optimal value bounds for nonconvex parametric nonlinear programs, Ph.D. dissertation, School of Engineering and Applied Science, George Washington Univ., Washington, DC (1985).

    Google Scholar 

Important relevant works not cited

  1. A.M. Geoffrion, Objective function approximation in mathematical programming, Math. Programming 13 (1977) 23–37.

    Google Scholar 

  2. E.R. Hansen and S. Sengupta, Global optimization using interval analysis, in:Interval Mathematics 1980, K. Nickel (ed.) (Academic Press, New York, 1980).

    Google Scholar 

  3. L.J. Mancini and G.P. McCormick, Bounding global minima, Math. Oper. Res. 1(1) (1976) 50–53.

    Google Scholar 

  4. L.J. Mancini and G.P. McCormick, Bounding global minima with interval arithmetic, Oper. Res. 27 (1979) 743–754.

    Google Scholar 

  5. G.P. McCormick, Locating an isolated global minimizer of a constrained nonconvex program, Math. Oper. Res. 5(3) (1980) 435–443.

    Google Scholar 

  6. R.R. Meyer, Two-segment separable programming, Management Sci. 25 (1979) 385–395.

    Google Scholar 

  7. S.M. Robinson, Bounds for error in the solution set of a perturbed linear program, Linear Algebra, Appl. 6 (1973) 69–81.

    Google Scholar 

  8. S.M. Robinson, Computable error bounds for nonlinear programming, Math. Programming 5(2) (1973) 235–242.

    Google Scholar 

  9. S.M. Robinson, Perturbed Kuhn-Tucker points and rates of convergence for a class of nonlinear programming algorithms, Math. Programming 7(1) (1974) 1–16.

    Google Scholar 

  10. M.H. Stern and D.M. Topkis, Rates of stability in nonlinear programming, Oper. Res. 24 (1976) 462–476.

    Google Scholar 

  11. L.S. Thakur, Error analysis for convex separable programs: The piecewise linear approximation and the bounds on the optimal objective value, SIAM J. Appl. Math. 34 (1978) 704–714.

    Google Scholar 

  12. L.S. Thakur, Error analysis for convex separable programs: Bounds on the optimal solution and the dual optimal solution, J. Math. Anal. Appl. 75 (1980) 486–494.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

Research supported by National Science Foundation Grant ECS 86-19859 and Grant N00014-89-J-1537, Office of Naval Research.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Fiacco, A.V. Global multi-parametric optimal value bounds and solution estimates for separable parametric programs. Ann Oper Res 27, 381–395 (1990). https://doi.org/10.1007/BF02055203

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02055203

Keywords

Navigation