Auflistung Stochastic Programming E-print Series (SPEPS) nach Titel
Anzeige der Publikationen 172-191 von 240
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2017-04-19BuchQuantitative Stability Analysis for Minimax Distributionally Robust RiskOptimization This paper considers distributionally robust formulations of a two stage stochastic programmingproblem with the objective of minimizing a distortion risk of the minimal cost incurred at the secondstage.We carry out stability ...
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2012-10-13BuchQuantitative Stability Analysis of Stochastic Generalized Equations We consider the solution of a system of stochastic generalized equations (SGE) where theunderlying functions are mathematical expectation of random set-valued mappings. SGE hasmany applications such as characterizing ...
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2000-12-20BuchQuantitative stability in stochastic programming Quantitative stability of optimal values and solution sets to stochastic programming problems is studied when the underlying probability distribution varies in some metric space of probability measures. We give conditions ...
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2007-12-07BuchQuantitative stability of fully random mixed-integer two-stage stochastic programs Mixed-integer two-stage stochastic programs with fixed recourse matrix, random recourse costs, technology matrix, and right-hand sides areconsidered. Quantitative continuity properties of its optimal value and solution set ...
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2014-12-30BuchQuasi-Monte Carlo methods for linear two-stage stochastic programming problems Quasi-Monte Carlo algorithms are studied for generating scenarios to solve two-stage linear stochastic programming problems. Their integrands are piecewise linear-quadratic, but do not belong to the function spaces ...
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2000-03-21BuchRandom lsc functions Random lsc (lower semicontinuous) functions can be indentified with a vector-valued random variable by means of an appropriate scalarization. It is shown that stationarity, ergodicity and independence properties are preserved ...
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2000-02-07BuchRandom lsc functions An ergodic theorem for random lsc functions is obtained by relying on a (novel) 'scalarization' of such functions. In the process, Kolmogorov's extension theorem for randon lsc functions is established. Applications to ...
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2010-06-04BuchReformulation of general chance constrained problems using the penalty functions We explore reformulation of nonlinear stochastic programs with several joint chance constraints by stochastic programs with suitably chosenpenalty-type objectives. We show that the two problems are asymptotically equivalent. ...
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2002-08-16BuchRisk aversion via excess probabilities in stochastic programs with mixed-integer recourse We consider linear two-stage stochastic programs with mixed-integer recourse. Instead of basing the selection of an optimal first-stage solution on expected costs alone, we include into the objective a risk term reflecting ...
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2001-10-04BuchRisk measures for income streams A new measure of risk is introduced for a sequence of random incomes adapted to some filtration. This measure is formulated as the optimal net present value of a stream of adaptively planned commitments for consumption. ...
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2015-09-16BuchRisk measures for vector-valued returns Portfolios, which are exposed to different currencies, have separate and different returns ineach individual currency and are thus vector-valued in a natural way.This paper investigates the natural domain of these risk ...
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2009-10-16BuchRisk-Averse Two-Stage Stochastic LinearProgramming: Modeling and Decomposition We formulate a risk-averse two-stage stochastic linear programming problem in which unresolved uncertainty remains after the second stage. The objective function is formulated as a composition of conditional risk measures.We ...
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2000-03-27BuchRobust path choice in networks with failures The problem of adaptive routing in a network with failures is considered. The network may be in one of finitely many states characterized by different travel times along the arcs, and transitions between the states occur ...
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2006-10-27BuchRobust solution and risk measures for a supply chain planning problem under uncertainty We consider a strategic supply chain planning problem formulated as a two-stageStochastic Integer Programming (SIP) model. The strategic decisions include sitelocations, choices of production, packing and distribution ...
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2010-10-20BuchSampling-based decomposition methods for risk-averse multistage programs We define a risk averse nonanticipative feasible policy for multistage stochastic programsand propose a methodology to implement it. The approach is based on dynamic programmingequations written for a risk averse formulation ...
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2017-02-21BuchScenariao Reduction Revisited: Fundamental Limits and Gurarantees The goal of scenario reduction is to approximate a given discrete distributionwith another discrete distribution that has fewer atoms. We distinguishcontinuous scenario reduction, where the new atoms may be chosen freely, ...
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2006-10-26BuchScenario reduction in stochastic programming with respect to discrepancy distances Discrete approximations to chance constrained and mixed-integer two-stage stochastic programs require moderately sized scenario sets. The relevant distances of (multivariate) probability distributions for deriving quantitative ...
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2000-08-14BuchScenario reduction in stochastic programming: An approach using probability metrics Given a convex stochastic programming problem with a discrete initial probability distribution, the problem of optimal scenario reduction is stated as follows: Determine a scenario subset of prescribed cardinality and a ...
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2006-03-31BuchScenario tree modelling for multistage stochastic programs An important issue for solving multistage stochastic programs consists inthe approximate representation of the (multivariate) stochastic input process inthe form of a scenario tree. In this paper, forward and backward ...
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2008-04-05BuchScenario tree reduction for multistage stochastic programs A framework for the reduction of scenario trees as inputs of (linear) multistage stochastic programs is provided such that optimal values and approximate solution sets remain close to each other. The argument is based on ...