Results 241 to 250 of about 295,852 (287)

Stochastic Programming

1972
Publisher Summary This chapter discusses stochastic programming. The chapter reviews the relationship between the feasibility of vectors x and the parameters. Kall's theorem, optimality, and convexity are reviewed. Decision regions for optimality are reviewed. If there are no degenerate solutions, then decision regions do not overlap, but two adjacent
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Stochastic Programs with Recourse

SIAM Journal on Applied Mathematics, 1967
Abstract : So far the study of stochastic programs with recourse has been limited to the case (called by G. Dantzig programming under uncertainty) when only the right-hand sides or resources of the problem are random. In this paper the authors extend the theory to the general case when essentially all the parameters involved are random.
Walkup, D. W., Wets, R. J.-B.
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Stochastic Integer Programming.

1997
no abstract.
Stougie, L., van der Vlerk, M.H.
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Stochastic Programming.

The Journal of the Operational Research Society, 1998
J. M. Wilson, JR Birge, F Louveaux
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Infinite Horizon Stochastic Programs

SIAM Journal on Control and Optimization, 1986
A discrete time infinite horizon stochastic program is considered whose objective function is a sum of discounted expected costs of decisions at time t. It is supposed that a cost function is convex, the number of outcomes is finite and the decision at time t is effected only by t and the decision at time t-1.
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Stochastic Programming

1985
Proceedings of the IFIP Workshop on Stochastic Programming, Gargnano, Italy ...
ARCHETTI F., DI PILLO, Gianni, LUCERTINI M., E.D.S.   +3 more
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Distributionally Robust Stochastic Programming

SIAM Journal on Optimization, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A Stochastic Programming Model

Econometrica, 1963
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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STOCHASTIC CONCAVE DYNAMIC PROGRAMMING

Mathematics of the USSR-Sbornik, 1972
In this paper the methods of stochastic control processes are combined with considerations regarding convexity, which are characteristic for the deterministic models of a developing economy. As a result a stochastic theory is obtained, heavily resembling the deterministic one, but which can also take into account the influence of stochastic factors ...
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Stochastic programming and stochastic control

Trabajos de Estadistica y de Investigacion Operativa, 1975
We consider the passive and active approach to stochastic linear programming and mention also some alternative approaches. Stochastic control theory is discussed in its discrete version. The theory is illustrated with the help of econometric models for Indian economic planning. 1. Stochastic programming. 2. Stochastic control theory.
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