TY - JOUR AU - Fábián, Csaba AU - Gurka Dezsőné Csizmás, Edit Margit AU - Drenyovszki, Rajmund AU - Vajnai, Tibor AU - Kovács, Lóránt AU - Szántai, Tamás TI - A randomized method for handling a difficult function in a convex optimization problem, motivated by probabilistic programming JF - ANNALS OF OPERATIONS RESEARCH J2 - ANN OPER RES VL - Online first PY - 2019 SP - 1 EP - 32 PG - 32 SN - 0254-5330 DO - 10.1007/s10479-019-03143-z UR - https://m2.mtmt.hu/api/publication/30415406 ID - 30415406 N1 - EFOP-3.6.1-16-2016-00006 Published online: 21 January 2019 LA - English DB - MTMT ER - TY - JOUR AU - Vizvári, Béla TI - The integer programming background of a stochastic integer programming algorithm of Dentcheva-Prekopa-Ruszczynski JF - OPTIMIZATION METHODS & SOFTWARE J2 - OPTIM METHOD SOFTW VL - 17 PY - 2002 IS - 3 SP - 543 EP - 559 PG - 17 SN - 1055-6788 DO - 10.1080/1055678021000034017 UR - https://m2.mtmt.hu/api/publication/2584126 ID - 2584126 AB - This paper analyzes the algorithmic tools presented in [D. Dentcheva, A. Prekopa and A. Ruszczynski. Bounds for Probabilistic Integer Programming Problems, RUTCOR, Rutgers University, NJ, RRR 31-99; D. Dentcheva, A. Prekopa and A. Ruszczynski (2000). Concavity and efficient points of discrete distributions in probabilistic programming. Mathematical Programming, Ser. A , 89 , 55-77]. The emphasis is on the choice of Lagrange multipliers and the solution for the special case of independent random variables. LA - English DB - MTMT ER - TY - JOUR AU - Dentcheva, D AU - Prékopa, András AU - Ruszczyński, A TI - Concavity and efficient points of discrete distributions in probabilistic programming JF - MATHEMATICAL PROGRAMMING J2 - MATH PROGRAM VL - 89 PY - 2000 IS - 1 SP - 55 EP - 77 PG - 23 SN - 0025-5610 DO - 10.1007/PL00011393 UR - https://m2.mtmt.hu/api/publication/3230053 ID - 3230053 AB - We consider stochastic programming problems with probabilistic constraints involving integer-valued random variables. The concept of a p-efficient point of a probability distribution is used to derive various equivalent problem formulations. Next we introduce the concept of r-concave discrete probability distributions and analyse its relevance for problems under consideration. These notions are used to derive lower and upper bounds for the optimal value of probabilistically constrained stochastic programming problems with discrete random variables. The results are illustrated with numerical examples. © Springer-Verlag 2000. LA - English DB - MTMT ER - TY - CONF AU - Szántai, Tamás TI - Probabilistic constrained programming and distributions with given marginals. T2 - Distributions with given marginals and moment problems, Proceedings of the 3rd Conference on ''Distributions with Given Marginals and Moment Problems'', held at Czech Agricultural University, Prague, Czech Republic, September 2-6, 1996, eds ET - 0 PY - 1997 SP - 205 EP - 210 PG - 6 UR - https://m2.mtmt.hu/api/publication/2617153 ID - 2617153 N1 - WoS:hiba:A1997BJ67K00024 2022-07-19 10:48 típus nem egyezik LA - English DB - MTMT ER - TY - CONF AU - Szántai, Tamás ED - Yu, Ermoliev ED - R J-B, Wets TI - A computer code for solution of probabilistic constrained stochastic programming problems T2 - Numerical Techniques for Stochastic Programming Problems, Springer Series in Computational Mathematics PB - Springer Netherlands C1 - Heidelberg ET - 0 PY - 1988 SP - 229 EP - 235 PG - 7 UR - https://m2.mtmt.hu/api/publication/2694566 ID - 2694566 LA - English DB - MTMT ER - TY - JOUR AU - Szántai, Tamás TI - EVALUATION OF A SPECIAL MULTIVARIATE GAMMA-DISTRIBUTION FUNCTION. Stochastic Programming 84 Part I. TS - Stochastic Programming 84 Part I. JF - MATHEMATICAL PROGRAMMING STUDY J2 - MATH PROGRAM STUD VL - 27 PY - 1986 SP - 1 EP - 16 PG - 16 SN - 0303-3929 UR - https://m2.mtmt.hu/api/publication/2617018 ID - 2617018 N1 - http://link.springer.com/book/10.1007/BFb0121110 Megjegyzés-23941356 : Science; Mathematics, Applied Cited By :27 Export Date: 31 October 2018 CODEN: MPSTD AB - In this paper we describe two different methods for the calculation of the bivariate gamma probability distribution function. One of them is based on a direct numerical integration and the other on a series expansion in terms of Laguerre polynomials. In the multivariate case we propose a Monte Carlo method. Our method can be used for other types of multivariate probability distributions too. In the special case of the multivariate normal distribution the computer experiments show that our method has the same efficiency as other known methods. We briefly describe the possible applications of the proposed algorithms in stochastic programming. LA - English DB - MTMT ER - TY - THES AU - Szántai, Tamás TI - Többdimenziós valószínűség-eloszlásokkal kapcsolatos valószínűségek numerikus meghatározásáról PY - 1985 SP - 122 UR - https://m2.mtmt.hu/api/publication/2617134 ID - 2617134 N1 - Source: PublEx LA - Hungarian DB - MTMT ER - TY - CHAP AU - Prékopa, András AU - Ganczer, Sándor AU - Deák, István AU - Patyi, Károly ED - M.A.H., Dempster TI - The stabil stochastic programming model and its experimental application to the electrical energy sector of the Hungarian economy T2 - Stochastic programming PB - Academic Press CY - London SN - 0122082508 T3 - Institute of Mathematics and Its Applications conference series PY - 1980 SP - 369 EP - 385 PG - 17 UR - https://m2.mtmt.hu/api/publication/30449452 ID - 30449452 LA - English DB - MTMT ER - TY - JOUR AU - Prékopa, András AU - Szántai, Tamás TI - An optimal regulation of a storage level with application to the water level regulation of a lake JF - EUROPEAN JOURNAL OF OPERATIONAL RESEARCH J2 - EJOR VL - 3 PY - 1979 IS - 3 SP - 175 EP - 189 PG - 15 SN - 0377-2217 DO - 10.1016/0377-2217(79)90137-1 UR - https://m2.mtmt.hu/api/publication/2617016 ID - 2617016 AB - In [10] a system of stochastic programming models was introduced for the optimal control of a storage level. Each model in this system serves to determine the optimal policy for only one period ahead though the time horizon consists of many future periods. The optimal control thus obtained can be considered an open loop control methodology. The main purpose of this paper is to present an application by giving an optimal control method for the regulation of the water level of Lake Balaton in Hungary. By solving almost 600 stochastic programming problems we analyze what would have happened if we had controlled the water level using our method between 1922 and 1970, where one decision period is one month. The numerical results show that the proposed control methodology works quite well in this case. © 1979. LA - English DB - MTMT ER - TY - JOUR AU - Prékopa, András AU - Szántai, Tamás TI - Flood control reservoir system design using stochastic programming JF - MATHEMATICAL PROGRAMMING STUDY J2 - MATH PROGRAM STUD VL - 9 PY - 1978 SP - 138 EP - 151 PG - 14 SN - 0303-3929 UR - https://m2.mtmt.hu/api/publication/2617014 ID - 2617014 LA - English DB - MTMT ER - TY - JOUR AU - Prékopa, András AU - Szántai, Tamás TI - NEW MULTIVARIATE GAMMA DISTRIBUTION AND ITS FITTING TO EMPIRICAL STREAMFLOW DATA JF - WATER RESOURCES RESEARCH J2 - WATER RESOUR RES VL - 14 PY - 1978 IS - 1 SP - 19 EP - 24 PG - 6 SN - 0043-1397 DO - 10.1029/WR014i001p00019 UR - https://m2.mtmt.hu/api/publication/2617015 ID - 2617015 N1 - Cited By :38 Export Date: 31 October 2018 AB - A new multivariate gamma distribution is presented which can successfully be fitted to empirical data where the one‐dimensional marginal distributions are gamma distributions with prescribed parameters and the correlations are nonnegative. It is not intended to give explicit formulae either for the joint density or for the joint characteristic function of the random variables. Our representation of the individual gamma‐distributed random variables will be used for simulation, with the aid of which we approximate probabilities of sets in higher‐dimensional spaces. Since streamflow and other hydrological data frequently follow gamma distribution and also they are frequently stochastically dependent, our multivariate distribution and fitting technique seems to be of particular interest from the hydrological point of view. Copyright 1978 by the American Geophysical Union. LA - English DB - MTMT ER -