Stochastic programming
In the field of mathematical optimization, stochastic programming is a framework for modeling optimization problems that involve uncertainty. A stochastic program is an optimization problem in which some or all problem parameters are uncertain, but follow known probability distributions. This framework contrasts with deterministic optimization, in which all problem parameters are assumed to be known exactly. The goal of stochastic programming is to find a decision which both optimizes some criteria chosen by the decision maker, and appropriately accounts for the uncertainty of the problem parameters. Because many real-world decisions involve uncertainty, stochastic programming has found applications in a broad range of areas ranging from finance to transportation to energy optimization.
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AIMMSAndrzej Piotr RuszczyńskiBenders decompositionCOIN-ORCatalog of articles in probability theoryChance-constrained portfolio selectionChannel coordinationCorrelation gapDarinka DentchevaDynamic programmingExtended Mathematical ProgrammingFortSPGeneral Algebraic Modeling SystemGeorge DantzigHadamard derivativeLINDOLinear programmingList of numerical analysis topicsList of probability topicsMPS (format)Mathematical optimizationNaum Z. ShorOpen energy system modelsOptimal designOutline of financePortfolio optimizationR. Tyrrell RockafellarRobust optimizationRoger J-B WetsSAMPLSecond-order cone programmingSmartDOSoftware tools for stochastic programmingStochastic dominanceStochastic dynamic programmingStochastic linear program
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Stochastic programming
In the field of mathematical optimization, stochastic programming is a framework for modeling optimization problems that involve uncertainty. A stochastic program is an optimization problem in which some or all problem parameters are uncertain, but follow known probability distributions. This framework contrasts with deterministic optimization, in which all problem parameters are assumed to be known exactly. The goal of stochastic programming is to find a decision which both optimizes some criteria chosen by the decision maker, and appropriately accounts for the uncertainty of the problem parameters. Because many real-world decisions involve uncertainty, stochastic programming has found applications in a broad range of areas ranging from finance to transportation to energy optimization.
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In the field of mathematical o ...... tation to energy optimization.
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Стохасти́ческое программи́рова ...... на каждый случайный результат.
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في مجال النمذجة، تعتبر البرمجة ...... ر معلومات مفيدة لمتخذي القرار.
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1,000,493,844
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In the field of mathematical o ...... tation to energy optimization.
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Стохасти́ческое программи́рова ...... в некотором смысле оптимально.
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في مجال النمذجة، تعتبر البرمجة ...... ر معلومات مفيدة لمتخذي القرار.
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Stochastic programming
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Стохастическое программирование
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برمجة عشوائية
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