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Neuere Entwicklung auf dem Gebiet der stochastischen Programmierung

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Part of the Proceedings in Operations Research book series (ORP, volume 1973)

Zusammenfassung

Die Vielzahl der Problemstellungen, die sich in der Form beschreiben lassen, hat u.a. dazu geführt, daß die mathematische Programmierung, d.h. die Lösung von Aufgaben des Types (1), zu einem der umfangreichsten Gebiete des Operations Research entwickelt hat.

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Literaturverzeichnis

  1. 1.
    Avriel, M.J.; Wilde, D.J.: “Stochastic Geometric Programming” in: Proc. of the Princeton Symp. on Math. Prog., Princeton 1970, S. 73–91Google Scholar
  2. 2.
    Barron, F.H.: “A Chance Constrained Optimization Model for Risk”, OMEGA, Vol. 1 (1973) No. 3, S. 363–366CrossRefGoogle Scholar
  3. 3.
    Bawa, V.S.: “On Chance Constrained Progranming Problems with Joint Constraints”, Mgt. Sc. Vol.19 (1973) No. 11, S. 1326–1331CrossRefGoogle Scholar
  4. 4.
    Bereanu, B.: “Programmation Stochastique et quelques-unes de ses Applications Economiques”, Publications Econométriques, Vol. V (1972), S. 143–161Google Scholar
  5. 5.
    Bereanu, B.: “On the Use of Computers in Planning under Conditions of Uncertainty”, Int. Symposium on Applications of Computers and Operations Research, Washington, 1973Google Scholar
  6. 6.
    Bereanu, B.: “The Continuity of the Optimum in Parametric Programming and Applications to Stochastic Programming”, Report Nr. 7305, Bucharest 12, 1973Google Scholar
  7. 7.
    Bereanu, B.: “Distribution-free Optinal Solutions in Stochastic Linear”, Report Nr. 7303, Bucharest 12, 1973Google Scholar
  8. 8.
    Bühler, W.; Dick, R.: “Stochastische Lineare Programmierung”, Zeitschrift für Betriebswirtschaft Nr. 2, Wiesbaden 1973Google Scholar
  9. 9.
    Bühler, W.; Dick, R.: “Stochastische Lineare Optimierung”, Zeitschrift für Betriebswirtschaft Nr. l0, Wiesbaden 1972Google Scholar
  10. 10.
    Bühler, W.: “Zur Lösung eines Zwei-Stufen-Risiko Modells der Stochastischen Linearen Optimierung”, Proceedings in Operations Research, Würzburg-Wien 1971Google Scholar
  11. 11.
    Charnes, A.: “Deterministic Equivalents for Optimizing and Satisfying under Chance Constraints”, Oper.Res., 11, 1963, S. 18–39CrossRefGoogle Scholar
  12. 12.
    Charnes, A.; Kirby, M.J.L.: “Some Special P-Models in Chanoe-Canstrained Programming”, Man.Science, 14, 1967, S. 183–195Google Scholar
  13. 13.
    Dantzig, G.B.; Madansky, A.: “On the Solution of Two-Stage Linear Programs under Uncertainty, Proceeding of the Fourth Berkely Symposium on Mathematical Statistics and Probability”, hrsg. von J. Neyman, Berkeley 1961, S. 165–176Google Scholar
  14. 14.
    Dinkelbach, W.: “Zur Frage Unternehmerischer Zielsetzungen bei Entscheidungen unter Risiko”, Zur Theorie des Absatzes, Wiedbaden 1973Google Scholar
  15. 15.
    Dragomirescu, M.: “An Algorithm for the Minimunt-Risk Problem of Stochastic Programming” Operations Research, Vol. 20 (1972), S. 154–164CrossRefGoogle Scholar
  16. 16.
    Dürr, W.: “Stochastische programmierungsmodelle als Vektormaximumprobleme”, Proceedings in Operations Research, Würzburg-Wien 1971Google Scholar
  17. 17.
    Ewbank, J.B.; Foote, B.L.; Hiller, J.K.: “A Method for the Solution of the Distribution Problem of Stochastic linear Programming”, Research Report R-72–1, Oklahoma 1972Google Scholar
  18. 18.
    Fäber, M.M.: “Stochastisches Programmieren”, Würzburg-Wien 1970Google Scholar
  19. 19.
    Garstka, S. J.: “Stochastic Programs with Recourse: Random Recourse Costs only”, Mgt Sc. Vol. 19 (1973) No. 7Google Scholar
  20. 20.
    Garstka, S.J.; Rutenberg, D.P.: “Computation in Discrete Stochastic Programs with Recourse”, Operations Research, Vol. 21 (1973), S. 112–123CrossRefGoogle Scholar
  21. 21.
    Kall, P.: “Der gegenwärtige Stand der Stodiastischen programmierung”, Unternehmensforschung 9 (1965), S. 238–249CrossRefGoogle Scholar
  22. 22.
    Parikh, S.C.: “Equivalent Stodiastic Linear Programs”, SIAM, Vol.18 (1970) S. 1–5Google Scholar
  23. 23.
    Prékopa, A.: “Contributions to the Theory of Stochastic Programming”, Mathematical Prograrmdng 4 (1973), S. 202–221CrossRefGoogle Scholar
  24. 24.
    Rödder, W.: “Lösungsvorschläge für stochastische Zielprogramme”, Proceedings in Operations Research, Würzburg-Wien 1971Google Scholar
  25. 25.
    Rutenberg, D.P.: “Risk Aversion in Stochastic Programming with Recourse”, Operations Research, Vol. 21 (1973) S. 377–379CrossRefGoogle Scholar
  26. 26.
    Sengupta, J.K.: “Chance-Constrained Linear Programming with Chi-Square Type Deviates”, Mgt. Sc. Vol 19 (1972) No. 3, S. 337–349CrossRefGoogle Scholar
  27. 27.
    Sengupta, J.K.: “Stochastic Programming, Methods and Applications”, Amsterdam-New York 1972Google Scholar
  28. 28.
    Slyke, R. van; Wets, R.J.B.: “L-Shaped linear Programs with Applications to Optimal Control and Stochastic Programming”, SIAM, Appl. Vol. 17 (1969), S. 638–663CrossRefGoogle Scholar
  29. 29.
    Smith, D.V.: “Decision Rules in Chance-Constrained Programming: some Experimental Comparisons”, Mgt. Sc. Vol. 19 (1973) No. 6, S. 688–701CrossRefGoogle Scholar
  30. 30.
    Streitferdt, L.: “Zur Lösung einiger spezieller Verteilungsprobleme der Stochastischen Programmierung”, Proceedings in Operations Research, Würzburg 1972Google Scholar
  31. 31.
    Tintner, G.; Rama Sastry, M.V.: “A Note on the Use of Nonparametric Statistics in Stochastic Linear Programming”, Mgt. Sc. Vol. 19 (1972), S. 205–210CrossRefGoogle Scholar
  32. 32.
    Vajda, S.: “Mathematical Programming”, Reading, New York 1961Google Scholar
  33. 33.
    Vajda, S.: “Probabilistic Programming”, New York 1971Google Scholar
  34. 34.
    Weisnen, J.; Holzman, A.G.: “Engineering Design Optimization under Risk”, Mgt. Sc. Vol.19 (1972), S. 235–249CrossRefGoogle Scholar
  35. 35.
    Werner, M.: “Ein Lösungsansatz für ein spezielles zweistufiges Stochastisches Optimierungsproblem”, Zeitschrift für Operations Research, Band 17, 1973, S. 119–128, WürzburgCrossRefGoogle Scholar
  36. 36.
    Wets, R.J.B.: “Characterization Theorems for Stochastic Programs”, Mathematical Programming 2 (1972), S. 166–175CrossRefGoogle Scholar
  37. 37.
    Wets, R.J.B.: “Programming under Uncertainty: The Complete Problem”, Zeitschr.f.W.Th. u. verw. Geb., Vol. 4 (1966), S. 316–339CrossRefGoogle Scholar
  38. 38.
    Williams, A.C.: “Nonlinear Acrtivityanalysis and Duality”, Math. Progr., Prinœton 1970, S. 163–177Google Scholar
  39. 39.
    Wilson, D.: “An (a priori) Bounded Model for Transportation Problems with Stochastic Demand and Integer Solutions”, AIIE Transaction, Vol. 4 (1972), No. 3Google Scholar
  40. 40.
    Ziemba, W.T.: “Duality Relations, Certainty Equivalents and Bounds for Convex Stochastic Programs with Simple Recourse”, Cahiers du centre d’études de recherche Operationelle, Vol. 13 (1971), No. 2Google Scholar
  41. 41.
    Ziemba, W.T.: “Transforming Stochastic Dynamic Programming Problems into Nonlinear Programs”, Mgt. Sc. Vol. 17 (1971), S. 450–462CrossRefGoogle Scholar
  42. 42.
    Zimmermann, H.J.; Pollatschek, M.A.: “Distribution Functions of the Optimum of Linear Programming with Randomly Distributed Right-Hand Side”, Angewandte Informatik, 1973, Heft 10Google Scholar
  43. 43.
    Zimmermann, H. J.; Pollatschek, M.A.: “A Computer-Oriented Approach to Characteristic Functions of Pseudo- Boolean Systems”, Angewandte Informatik, 1973, Heft 9Google Scholar
  44. 44.
    Zimmermann, H.J.; Pollatschek, M.A.: “The Domain of the “Resource-Vector” as an Aid to Decision Making in Stochastic 0/1 Programming”, Operations Research Verfahren, Vol. XIV, (1972), S. 390–398Google Scholar
  45. 45.
    Zinn, C.D.; Foote, B.L.: “An Algorithm for the Solution of the Distribution Problem of Probabilistic Linear Programming”, Research Report R-72–2, Oklahoma 1972Google Scholar

Copyright information

© Physica-Verlag, Rudolf Liebing KG, Würzburg 1974

Authors and Affiliations

  1. 1.AachenDeutschland

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