Results 241 to 250 of about 297,933 (284)

Introduction to Stochastic Programming

Journal of the Operational Research Society, 1998
(1998). Introduction to Stochastic Programming. Journal of the Operational Research Society: Vol. 49, No. 8, pp. 897-898.
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Discrete Stochastic Programming

Management Science, 1968
A method is presented for solving linear programming problems where (any number of) the functional, restraint, and input-output coefficients are subject to discrete; probability distributions. The objective function is formulated in terms of variance and/or expectation.
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The Value of Information and Stochastic Programming

Operations Research, 1970
The problem of planning under uncertainty has many aspects; in this paper we consider the aspect that has to do with evaluating the state of information. We address ourselves to the question of how much better (i.e., how much more profitable) we could expect our plans to be if somehow we could know at planning time what the outcomes of the uncertain ...
Mordecai Avriel, A. C. Williams
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A Stochastic Programming Model

Econometrica, 1963
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Scenarios for Multistage Stochastic Programs

Annals of Operations Research, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dupacova, Jitka, Consigli, Giorgio, Wallace, S W   +2 more
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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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Optimality functions in stochastic programming

Mathematical Programming, 2011
A stochastic programming problem is considered with nonlinear and possibly non-convex expected value objective and constraint functions. The concept of an optimality function is extended to stochastic programs, and applied to evaluate the quality of a candidate solution by means of confidence intervals.
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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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Stochastic Programming

Journal of the Operational Research Society, 1998
M Banerjea-Brodeur, J-F Cordeau, G Laporte, A Lasry, Z Degraeve, F Roodhooft, G Baltas, P Doyle, J C S Brandão, A Mercer, Y V Hui, R Wild, T W Jonsbråten, R Morabito, S Morales, V Lotfi, J Sarkis, J H Semple, M Ben-Daya, M Makhdoum, K Iwamura, B Liu, E A Silver, D Costa, A Byrne, M Sniedovich, J Figueira, H M'Silti, B Srivastava, C Tofallis, A Taket, A Prekopa, J M Wilson   +32 more
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Stochastic Programming

Journal of the Operational Research Society, 1995
Kiriakos Vlahos, Peter Kall, Stein W. Wallace   +2 more
  +6 more sources