Auflistung Stochastic Programming E-print Series (SPEPS) nach Titel
Anzeige der Publikationen 1-20 von 240
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2007-06-03BuchA Branch-and-Bound Method for Multistage Stochastic Integer Programs with Risk Objectives We identify multistage stochastic integer programs with risk objectives where the related wait-and-see problems enjoy similar separability as in the risk neutral case. For models belonging to this classwe present a solution ...
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2004-02-21BuchA branch-and-cut algorithm for the stochastic uncapacitated lot-sizing problem This paper addresses a multi-stage stochastic integer programming formulation of the uncapacitated lot-sizing problem under uncertainty. We show that the classical $(\mathcal{l}, S)$ inequalities for the deterministic ...
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2006-10-27BuchA branch-and-cut algorithm for two-stage stochastic mixed-binary programs with continuous first-stage variables This paper presents a branch-and-cut method for two-stage stochastic mixed-integer programming (SMIP) problems with continuous first-stage variables. This method is derived based on disjunctive decomposition(D2) for SMIP, ...
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2002-10-24BuchA branch-and-price algorithm for multi-stage stochastic integer programming with application to stochastic batch-sizing problems In this paper we present a branch-and-price method to solve special structured multi-stage stochastic integer programming problems. We validate our method on two different versions of a multi-stage stochastic batch-sizing ...
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2005-01-10BuchA Branch-Reduce-Cut Algorithm for the Global Optimization of Probabilistically Constrained Linear Programs We consider probabilistic constrained linear programs with general distributions for the uncertain parameters. These problems generally involve non-convex feasible sets. We develop a branch and bound algorithm that searches ...
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2004-10-02BuchA class of stochastic programs with decision dependent uncertainty The standard approach to formulating stochastic programs is based on the assumption that the stochastic process is independent of the optimization decision. We address a class of problems where the optimization decisions ...
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2015-04-22BuchA Comment on "Computational Complexityof Stochastic Programming Problems" Although stochastic programming problems were always believed to be computationally chal-lenging, this perception has only recently received a theoretical justification by the seminal workof Dyer and Stougie (Mathematical ...
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2005-12-29BuchA Comparative Study of Decomposition Algorithms for Stochastic Combinatorial Optimization This paper presents comparative computational results using three decomposition algorithms on a battery of instances drawn from three different applications. In order to preserve the commonalities among the algorithms in ...
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2010-06-04BuchA comparison of sample-based stochastic optimal control methods In this paper, we compare the performance of two scenario-based numerical methods to solve stochastic optimal control problems: scenario trees and particles. The problem consists in finding strategies to control a dynamicalsystem ...
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2009-05-19BuchA computational study of a solver system for processing two-stage stochastic linear programming problems Formulation of stochastic optimisation problems and computational algorithms for their solution continue to make steady progress as can be seenfrom an analysis of many developments in this field. The edited volume by Wallace ...
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2010-11-29BuchA computational study of a solver system forprocessing two-stage stochastic linearprogramming problems
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2000-01-20BuchA Dynamic Asset Allocation Model with Downside Risk Control This paper presents a new stochastic model for investment. The investor's objective is to maximize the expected growth rate while controlling for downside risk. Assuming lognormally distributed prices, the strategy that ...
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2008-03-06BuchA dynamic day-ahead paratransit planning problem We consider a dynamic planning problem for the transport of elderly and disabled people. The focus is on a decision to make one day ahead:which requests to serve with own vehicles, and which ones to assign to subcontractors, ...
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2004-02-19BuchA factor 1/2 approximation algorithm for a class of two-stage stochastic mixed-integer programs Abstract We introduce the two-stage stochastic maximum-weight matching problem and demonstrate that this problem is NP-complete. We give a factor 1/2 approximation algorithm and prove its correctness. We also provide a ...
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2000-07-04BuchA finite branch and bound algorithm for two-stage stochastic integer programs This paper addresses a general class of two-stage stochastic programs with integer recourse and discrete distributions. We exploit the structure of the value function of the second stage integer problem to develop a novel ...
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2011-09-13BuchA gradient formula for linear chance constraints under Gaussian distribution We provide an explicit gradient formula for linear chance constraints under a (possibly singular) multivariate Gaussian distribution. This formula allows one to reduce the calculus of gradients to the calculus of values ...
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2001-04-06BuchA heuristic for generating scenario trees for multistage decision problems In stochastic programming models we always face the problem of how to represent the random variables. This is particularly difficult with multidimensional distributions. We present an algorithm that produces a discrete ...
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2006-10-18BuchA JELS Stochastic inventory model with random demand A stochastic joint lot size model has been developed in which demand ofthe customer and the stock level of the vendor are assumed to be identicallydistributed continuous random variables. The effective ways for a ...
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2013-05-14BuchA mixed-integer stochastic nonlinear optimization problem with joint probabilistic constraints We illustrate the solution of a mixed-integer stochastic nonlinear optimization problem in an application of power management. In this application, a coupled system consisting of a hydro power station and a wind farm is ...
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2009-04-05BuchA model for dynamic chance constraints in hydro power reservoir management In this paper, a model for (joint) dynamic chance constraints is proposed and applied to an optimization problem in water reservoir management. The model relies on discretization of the decision variables but keeps the ...