D
Stochastic Programming, Decision Problems
and Algorithmic Solution
  1. On Probabilistic Constrained Programming. Proceedings of the Princeton Symposium on Mathematical Programming. Princeton University Press, Princeton, NJ 1970, 113-138.
  2. On Optimization of Stochastic Systems, Doctor of Mathematical Sciences Thesis, Budapest 1970 (in Hungarian, 160 pages).
  3. A Class of Stochastic Programming Decision Problems. Mathematicsche Operationsforschung und Statistik 3(1972) 349-354.
  4. Contributions to the Theory of Stochastic Programming. Mathematical Programming 4(1973) 202-221.
  5. Programming under Probabilistic Constraints with a Random Technology Matrix. Mathematische Operationsforschung und Statistik 5(1974) 109-116.
  6. The STABIL Stochastic Programming Model and its Experimental Application to the Electrical Energy Sector of Hungarian Economy in: Stochastic Programming, Proceedings of the International Conference on Stochastic Programming, Oxford, England, 1974 (edited by M.A.H. Dempster). Academic Press 1980, 369-385. With I. Deák, S. Ganczer, K. Patyi.
  7. On Multi-Stage Stochastic Programming. In: Progress in Operations Research, Proceedings of the International Conference on Operations Research, Eger, Hungary 1974. Colloquia Mathematica Societatis János Bolyai 12 (A. Prékopa, editor). North Holland Publishing Company 1976, 733-755. With T. Szántai.
  8. The STABIL Stochastic Programming Model and its Experimental Application to the Electrical Energy Industry of Hungary, Applied Mathematical Papers (Alkalmazott Matematikai Lapok) 1(1975) 3-22 (in Hungarian). With I. Deák, S. Ganczer, K. Patyi.
  9. Optimal Control of a Storage Level Using Stochastic Programming. Problems of Control and Information Theory 4(1975) 193-204. With T. Szántai.
  10. Dynamic Type Stochastic Programming Models. In: Studies on Mathematical Programming, Proceedings of the International Conference on Mathematical Programming, Mátrafüred, Hungary, 1975. Mathematical Methods of Operations Research Vol 1 (A.Prékopa, editor), Publ. House of the H.A.S., Budapest, 1976, 127-145.
  11. The Use of Stochastic Programming for the Solution of Some Problems in Probability and Statistics, In: Extremal Methods and Systems Analysis, Proceedings of an International Conference in Honour of A. Charnes' Sixtieth Birthday, Austin, Texas 1977. Lecture Notes in Economics and Mathematical Systems 174 (A.V. Fiacco, K.O. Kortanek, editors). Springer Verlag 1980, 522-536.
  12. Dynamic Type Stochastic Programming Models. In: Studies on Mathematical Programming, Proceedings of the IV International Conference on Mathematical Programming, Mátrafüred, Hungary 1975. Mathematical Methods of Operations Research I (A. Prékopa, editor). Publ. House of the H.A.S., Budapest, 1980, 127-145.
  13. Numerical Solution of Probabilistic Constrained Stochastic Programming Problems. In: Numerical Techniques for Stochastic Optimization (Yu. Ermoliev and R.J-B. Wets, editors). Springer, 1987, 123-139.
  14. Programming Under Probabilistic Constraint, and Maximizing a Probability under Constraints, Statistical Methods for Decision Processes (G.Hellwig, P.Kall, P.Abel, editors). Daimler-Benz, Stuttgart, Germany, 1994, 78-106.
  15. Programming under Probabilistic Constraint with Discrete Random Variables. In: New Trends in Mathematical Programming (F. Giannessi, T. Rapcsák, editors). Kluwer Academic Publishers, 1997, 235-257. With B. Vizvári, T. Badics.
  16. The use of Discrete Moment Bounds in Probabilistic Constrained Stochastic Programming Models. Annals of Operations Research 85 (1999) 21-38.
  17. Concavity and Efficient Points of Discrete Distributions in Probabilistic Programming. Math. Programming Ser.A 89(2000) 55-77. With D. Dentcheva, A. Ruszczyński.
  18. On convex probabilistic programming with discrete distributions. Nonlinear Analysis 47 (2001) 1997-2009. With D. Dentcheva, A. Ruszczyński.
  19. Bounds for probabilistic integer programming. Discrete Applied Mathematics 124 (2002) 55-65. With D. Dentcheva, A. Ruszczyński.
  20. A Multi-Objective, Probabilistic Constrained Stochastic Programming Model: An application of the duality theorem of linear programming. Mathematical Papers (Matematikai Lapok), New Series 11(2002-2003) 36-49(in Hungarian).
  21. A stochastic Programming Model to Find Optimal Sample Sizes to Estimate Unknown Parameters in an LP. Operations Research Letters 32 (2004) 59-67. With X. Hou.
  22. On Stages and Consistency Checks in Stochastic Programming. Operations Research Letters 33(2005) 171-175. With H. Gassmann.
  23. Convex Approximations in Stochastic Programming by Semidefinite Programming. Annals of Operations Research, to appear. With I. Deák, I. Pólik, T. Telaky.
  24. Uniform Quasi-Concavity in Probabilistic Constrained Stochastic Programming. Operations Research Letters 39(2011) 188-192. With K. Yoda, M. Subasi.