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SLP-IOR: A model management system for stochastic linear programming - system design -

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Optimization-Based Computer-Aided Modelling and Design

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References

  1. BIRGE, J. R., WETS, R. J.-B.: "Designing approximation schemes for stochastic optimization problems, in particular for stochastic programs with recourse", Math. Programming Stud. 27 (1986) 54–102.

    Google Scholar 

  2. BIRGE, J. R., DEMPSTER, M. A. H., GASSMANN, H., GUNN, E., KING, A. J., WALLACE, S. W.: "A standard input format for multiperiod stochastic linear programs", IIASA Working Paper WP-87-118 (1987).

    Google Scholar 

  3. BISSCHOP, J., MEERAUS, A.: "On the development of a general algebraic modeling system in a strategic planning environment", Math. Programming Stud. 20 (1982) 1–29.

    Google Scholar 

  4. BORELL, C.: "Convex set-functions in d-space", Periodica Math. Hungarica 6 (1975) 111–136.

    Google Scholar 

  5. BONCZEK, R.H., HOLSAPPLE, C. W., WHINSTON, A. B.: "Foundations of decision support systems", Academic Press (1981).

    Google Scholar 

  6. BROOKE, A., KENDRICK, D., MEERAUS, A.: "GAMS. A User's Guide", The Scientific Press, (1988).

    Google Scholar 

  7. DANTZIG, G. B., GLYNN, P.W.: "Parallel processors for planning under uncertainty", Technical Report SOL 88-8R, Department of Operations Research, Stanford University, (1989).

    Google Scholar 

  8. DEÁK, I.: "Multidimensional integration and stochastic programming", in Ermoliev, Y., Wets, R., J.-B., (eds.) Numerical Techniques for Stochastic Optimization, Springer-Verlag Berlin (1988) 187–200.

    Google Scholar 

  9. DOLK, D. R.: "A generalized model management system for mathematical programming", ACM Transactions on Mathematical Software 12 (1986) 92–125.

    Google Scholar 

  10. DOLK, D.R.: "Model management systems for operations research: A prospectus", in Mathematical Methods for Decision Support, ed. G. Mitra, Springer (1988) 347–373.

    Google Scholar 

  11. DOLK, D. R., KONSYNSKI, B. R.: "Knowledge representation for model management", IEEE Transactions on Software Engineering SE-10 (1984) 619–627.

    Google Scholar 

  12. DRUD, A. S.: "Interfaces between modeling systems and solution algorithms" in Mathematical Methods for Decision Support, ed. G. Mitra, Springer (1988) 187–196.

    Google Scholar 

  13. EDWARDS, J.: "A proposed standard input format for computer codes which solve stochastic programs with recourse", in Ermoliev, Y., Wets, R., J.-B., (eds.) Numerical Techniques for Stochastic Optimization, Springer-Verlag, Berlin (1988) 215–227.

    Google Scholar 

  14. ERMOLIEV, Y.: "Stochastic quasigradient methods and their application to systems optimization", Stochastics 9 (1983) 1–36.

    Google Scholar 

  15. FOURER, R., GAY, D. M., KERNIGHAN, B. W.: "A modeling language for mathematical programming", Management Science 36 (1990) 519–554.

    Google Scholar 

  16. FRAUENDORFER, K.: "Solving SLP recourse problems with arbitrary multivariate distributions — The dependent case", Mathematics of Op. Res. 13 (1988) 377–394.

    Google Scholar 

  17. FRAUENDORFER, K.: "A simplicial approximation scheme for convex two-stage stochastic programming problems", Manuscript, IOR University of Zürich (1989).

    Google Scholar 

  18. FRAUENDORFER, K., KALL, P.: "A solution method for SLP recourse problems with arbitrary multivariate distributions — The independent case", Probl. Control & Inform. Th. 17 (1988) 177–205.

    Google Scholar 

  19. GAIVORONSKI, A.: "Interactive program SQG-PC for solving stochastic programming problems on IBM/XT/AT compatibles-User Guide", IIASA Working Paper WP-88-11, (1988).

    Google Scholar 

  20. GEOFFRION, A.M.: "An introduction to structured modeling", Management Science 33 (1987) 547–588.

    Google Scholar 

  21. HIGLE, J.L., SEN, S.: "Stochastic decomposition: an algorithm for two-stage linear programs with recourse", SIE Technical Report 87-7, University of Arizona, Tucson (1988).

    Google Scholar 

  22. HIGLE, J.L., SEN, S.: "Statistical verification of optimality conditions", SIE Technical Report, University of Arizona, Tucson (1988).

    Google Scholar 

  23. HUERLIMANN, T., KOHLAS, J.: "LPL: A structured language for linear programming modeling", OR Spectrum 10 (1988) 55–63.

    Google Scholar 

  24. KALL, P.: "Approximations to stochastic programs with complete fixed recourse", Numer. Math. 22 (1974) 333–339.

    Google Scholar 

  25. KALL, P.: "Stochastic linear programming", Springer-Verlag, Berlin, (1976).

    Google Scholar 

  26. KALL, P.: "Computational methods for solving two-stage stochastic linear programming problems", ZAMP 30 (1979) 261–271.

    Google Scholar 

  27. KALL, P.: "Stochastic programs with recourse: An upper bound and the related moment problem", ZOR 31 (1987) A119–A141.

    Google Scholar 

  28. KALL, P.: "On approximation and stability in stochastic programming", in Guddat, J. et al. (eds.) Parametric Optimization and Related Topics, Akademie-Verlag, Berlin (1987) 387–407.

    Google Scholar 

  29. KALL, P.: "Stochastic programming with recourse: Upper bounds and moment problems", in Guddat, J. et al. (eds.) Advances in Mathematical Optimization, Akademie-Verlag, Berlin (1988) 86–103.

    Google Scholar 

  30. KALL, P.: "An upper bound for SLP using first and total second moments", Preprint, IOR University of Zürich (1989).

    Google Scholar 

  31. KALL, P.: "A review on approximations in stochastic programming", Preprint, IOR University of Zürich (1989).

    Google Scholar 

  32. KALL, P.: "Solution methods in stochastic programming — A review-", Preprint, IOR University of Zurich (1990).

    Google Scholar 

  33. KALL, P., STOYAN, D.: Solving stochastic programming problems with recourse including error bounds", Math. Operationsforsch. Statist., Ser. Optimization 13 (1982) 431–447.

    Google Scholar 

  34. KALL, P., RUSZCZYNSKI, A., FRAUENDORFER, K.: "Approximation techniques in stochastic programming", in Ermoliev, Y., Wets, R., J.-B., (eds.) Numerical Techniques for Stochastic Optimization, Springer-Verlag, Berlin (1988) 33–64.

    Google Scholar 

  35. KELLER, E.: "GENSLP: A program for generating input for stochastic linear programs with complete fixed recourse", Manuscript, IOR University of Zürich (1984).

    Google Scholar 

  36. KING, A., J.: "Stochastic programming problems: Examples from the literature", in Ermoliev, Y., Wets, R., J.-B., (eds.) Numerical Techniques for Stochastic Optimization, Springer-Verlag, Berlin (1988) 543–567.

    Google Scholar 

  37. KOMÁROMI, É.: "A dual method for probabilistic constrained problems", Math. Programming Stud. 28 (1986) 94–112.

    Google Scholar 

  38. LENARD, M. L.: "Structured model management", in Mathematical Methods for Decision Support, ed. G. Mitra, Springer (1988) 375–391.

    Google Scholar 

  39. MARSTEN, R. E.: The design of the XMP linear programming library", ACM Transactions on Mathematical Software 7 (1981) 481–497.

    Google Scholar 

  40. MAYER, J.: "A nonlinear programming method for the solution of a stochastic programming model of A. Prékopa", in Prékopa, A. (ed.) Survey of Mathematical Programming, North-Holland, Vol. 2 (1979) 129–139.

    Google Scholar 

  41. MAYER, J.: "Probabilistic constrained programming: A reduced gradient algorithm implemented on PC", IIASA Working Paper WP-88-39 (1988).

    Google Scholar 

  42. McALLISTER, P. H., STONE, J. C., DANTZIG, G.B.: "An interactive model management system: User interface and system design" Systems Optimization Laboratory, Stanford University, Technical Report SOL 90-3 (1990)

    Google Scholar 

  43. MITRA, G.: "Models for decision making: An overview of problems, tools and major issues", in Mathematical Methods for Decision Support, ed. G. Mitra, Springer (1988) 17–53.

    Google Scholar 

  44. MURTAGH, B. A., SAUNDERS, M. A.: "Large scale linearly constrained optimization", Math. Programming 14 (1978) 41–72.

    Google Scholar 

  45. MURTAGH, B. A., SAUNDERS, M. A.: "A projected Lagrangian algorithm and its implementation for sparse nonlinear constraints", Math. Progr.Study 16 (1982) 84–117.

    Google Scholar 

  46. PRÉKOPA, A.: "Logarithmic concave measures with application to stochastic programming", Acta. Sci. Math. 32 (1971) 301–316.

    Google Scholar 

  47. PRÉKOPA, A.: "Eine Erweiterung der sogenannten Method der zulässigen Richtungen der nichtlinearen Optimierung auf den Fall quasikonkaver Restriktionen", Math. Operationsforsch. Statist., Ser. Optimization 5 (1974) 281–293.

    Google Scholar 

  48. PRÉKOPA, A., GANCZER, S., DEÁK, I., PATYI, K.: "The STABIL stochastic programming model and its experimental application to the electricity production in Hungary", in Dempster, M.A.H. (ed.): Stochastic Programming, Academic Press, London (1980) 369–385.

    Google Scholar 

  49. PRÉKOPA, A.: "Numerical solution of probabilistic constrained programming problems", in Ermoliev, Y., Wets, R., J.-B., (eds.) Numerical Techniques for Stochastic Optimization, Springer-Verlag, Berlin (1988) 123–139.

    Google Scholar 

  50. RUSZCZYNSKI, A.: "A regularized decomposition method for minimizing a sum of polyhedral functions", Math. Programming 35 (1986) 309–333.

    Google Scholar 

  51. SCHITTKOWSKI, K.: "EMP: An expert system for mathematical programming", Mathematisches Institut, Universität Bayreuth, (1987).

    Google Scholar 

  52. SCHRAGE, L., CUNNINGHAM, K.: "Demo LINGO/PC: Language for INteractive General Optimization, version 1.04a", LINDO Systems Inc., Chicago (1988).

    Google Scholar 

  53. SIMONS, R.: "Mathematical programming modeling using MGG", IMA Journal of Mathematics in Management 1 (1987) 267–276.

    Google Scholar 

  54. SPRAGUE, R.H., CARLSON, E. D.: "Building effective decision support systems", Prentice-Hall (1982)

    Google Scholar 

  55. STRAZICKY, B.: "On an algorithm for solution of the two-stage stochastic programming problem", Methods. Oper. Res. 19 (1974) 142–156.

    Google Scholar 

  56. STRAZICKY, B.: "TWOSTAGE: A code of a basis decomposition method for stochastic programming", IIASA Working Paper WP-87-82 (1987).

    Google Scholar 

  57. SZÁNTAI, T.: "Calculation of the multivariate distribution function values and their gradient vectors", IIASA Working Paper WP-87-82 (1987).

    Google Scholar 

  58. SZÁNTAI, T.: "A computer code for solution of probabilistic-constrained stochastic programming problems", in Ermoliev, Y., Wets, R., J.-B., (eds.) Numerical Techniques for Stochastic Optimization, Springer-Verlag, Berlin (1988) 229–235.

    Google Scholar 

  59. WETS, R. J-B.: "Solving stochastic programs with simple recourse I", Department of Mathematics, University of Kentucky, Lexington (1974).

    Google Scholar 

  60. WETS, R. J-B.: "Solving stochastic programs with simple recourse", Stochastics 10 (1983) 219–242.

    Google Scholar 

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Adriaan Jacobus Maria Beulens Hans-Jürgen Sebastian

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Kall, P., Mayer, J. (1992). SLP-IOR: A model management system for stochastic linear programming - system design -. In: Beulens, A.J.M., Sebastian, HJ. (eds) Optimization-Based Computer-Aided Modelling and Design. Lecture Notes in Control and Information Sciences, vol 174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0040143

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  • DOI: https://doi.org/10.1007/BFb0040143

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