Browsing Stochastic Programming Eprint Series (SPEPS) by Title
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20040913BuchOn deviation measures in stochastic integer programming We propose extensions of traditional expectationbased stochastic integer programs to meanrisk models. Risk is measured by expected deviations of suitable random variables from their means or from preselected targets. We ...

20140507BuchOn Distributionally Robust Multiperiod Stochastic Optimization This paper considers model uncertainty for multistage stochastic programs. The data and information structure of the baseline model is a tree, on which the decision problem is defined. We consider ambiguity neighborhoods ...

20101019BuchOn joint probabilistic constraints with Gaussian coefficient matrix The paper deals with joint probabilistic constraints defined by a Gaussiancoefficient matrix. It is shown how to explicitly reduce the computation ofvalues and gradients of the underlying probability function to that of ...

20030930BuchOn Leland's option hedging strategy with transaction costs Nonzero transaction costs invalidate the BlackScholes (1973) arbitrage argument based on continuous trading. Leland (1985) developed a hedging strategy which modifies the BlackScholes hedging strategy with a volatility ...

20071207BuchOn Mstationary points for a stochastic equilibrium problem under equilibrium constraints in electricity spot market modeling Modeling several competitive leaders and followers acting in an electricity marketleads to coupled systems of mathematical programs with equilibrium constraints,called equilibrium problems with equilibrium constraints ...

20020502BuchOn Multiple Simple Recourse models We consider multiple simple recourse (MSR) models, both continuous and integer versions, which generalize the corresponding simple recourse (SR) models by allowing for a refined penalty cost structure for individual shortages ...

20091016BuchOn probabilistic constraints induced by rectangular sets and multivariate normal distributions In this paper, we consider optimization problems under probabilistic constraints which aredeﬁned by twosided inequalities for the underlying normally distributed random vector. Asa main step for an algorithmic solution ...

19991018BuchOn Rate of Convergence of Optimal Solutions of Monte Carlo Approximations of Stochastic Programs In this paper we discuss Monte Carlo simulation based approximations of a stochastic programming problem. We show that if the corresponding random functions are convex piecewise smooth and the distribution is discrete, ...

20061218BuchOn Rates of Convergence for Stochastic Optimization Problems Under NonI.I.D. Sampling In this paper we discuss the issue of solving stochastic optimization problems bymeans of sample average approximations. Our focus is on rates of convergence of estimators of optimal solutions and optimal values with respect ...

20080702BuchOn Stability of Multistage Stochastic Programs We study quantitative stability of linear multistage stochastic programs underperturbations of the underlying stochastic processes. It is shown that the optimalvalues behave Lipschitz continuous with respect to an ...

20080306BuchOn the convergence of stochastic dual dynamic programming and related methods We discuss the almostsure convergence of a broad class of sampling algorithms for multistage stochastic linear programs. We provide a convergence proof based on the ﬁniteness of the set of distinct cutcoefficients. This ...

20041227BuchOn the FortetMourier metric for the stability of Stochastic Optimization Problems, an example We consider the use of the FortetMourier metric between two probability measures to bound the error term made by an approximated solution of a stochastic program. After a short analysis of usual stability arguments, we ...

20111128BuchOn the Geometry of Acceptability Functionals In this paper we discuss the geometry of acceptability functionals or risk measures. The dependenceof the random variable is investigated ﬁrst. The main contribution and focus of this paper is to studyhow acceptability ...

20060320BuchOn twostage convex chance constrained problems In this paper we develop approximation algorithms for twostage convex chance constrainedproblems. Nemirovski and Shapiro [16] formulated this class of problems and proposed anellipsoidlike iterative algorithm for the ...

20061018BuchOptimal Hedging Strategies for MultiperiodGuarantees in the Presence of Transaction Costs:A Stochastic Programming Approach Multiperiod guarantees are often embedded in life insurance contracts. In this paper we consider the problem of hedging these multiperiod guarantees in the presence of transaction costs. We derive thehedging strategies ...

20170419BuchOptimal scenario generation and reduction in stochastic programming Scenarios are indispensable ingredients for the numerical solution of stochastic optimization problems. Earlier approaches for optimal scenario generation and reduction are based on stability arguments involving distances ...

20030618BuchOptimality and duality theory for stochastic optimization problems with nonlinear dominance constraints We consider a new class of optimization problems involving stochastic dominance constraints of second order. We develop a new splitting approach to these models, optimality conditions and duality theory. These results are ...

20040325BuchOptimization of Convex Risk Functions We consider optimization problems involving convex risk functions. By employing techniques of convex analysis and optimization theory in vector spaces of measurable functions we develop new representation theorems for risk ...

20020523BuchOptimization of simultaneous power production and trading by stochastic integer programming We develop a twostage stochastic integer programming model for the simultaneous optimization of power production and dayahead power trading. The model rests on mixedinteger linear formulations for the unit commitment ...

20030618BuchOptimization with stochastic dominance constraints We introduce stochastic optimization problems involving stochastic dominance constraints. We develop necessary and sufficient conditions of optimality and duality theory for theses models and we show that the Lagrange ...