نتایج جستجو برای: multistage stochastic programming

تعداد نتایج: 454319  

Journal: :civil engineering infrastructures journal 0
bita analui phd candidate, institute of statistics and operations research (isor), university of vienna, vienna, austria. raimund kovacevic phd, institute of statistics and operations research (isor), university of vienna, vienna,austria.

multistage stochastic programming is a key technology for making decisions over time in an uncertain environment. one of the promising areas in which this technology is implementable, is medium term planning of electricity production and trading where decision makers are typically faced with uncertain parameters (such as future demands and market prices) that can be described by stochastic proc...

Journal: :Journal of Computational and Applied Mathematics 2001

Journal: :international journal of smart electrical engineering 2015
mehdi farhadkhani

since the emergence of power market, the target of power generating utilities has mainly switched from cost minimization to revenue maximization. they dispatch their power energy generation units in the uncertain environment of power market. as a result, multi-stage stochastic programming has been applied widely by many power generating agents as a suitable tool for dealing with self-scheduling...

Journal: :Math. Program. 2005
Arjan Berkelaar Joaquim A. S. Gromicho Roy Kouwenberg Shuzhong Zhang

This paper presents a new and high performance solution method for multistage stochastic convex programming. Stochastic programming is a quantitative tool developed in the field of optimization to cope with the problem of decision-making under uncertainty. Among others, stochastic programming has found many applications in finance, such as asset-liability and bond-portfolio management. However,...

Journal: :Math. Program. 2008
Alexander Shapiro

In this paper we discuss computational complexity and risk averse approaches to two and multistage stochastic programming problems. We argue that two stage (say linear) stochastic programming problems can be solved with a reasonable accuracy by Monte Carlo sampling techniques while there are indications that complexity of multistage programs grows fast with increase of the number of stages. We ...

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