Volume 2004: Recent submissions
Now showing items 1-20 of 22
-
2004-12-27BuchOn the Fortet-Mourier metric for the stability of Stochastic Optimization Problems, an example We consider the use of the Fortet-Mourier 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 ...
-
2004-10-02BuchTwo-stage integer programs with stochastic right-hand sides We consider two-stage pure integer programs with discretely distributed stochastic right-hand sides. We present an equivalent superadditive dual formulation that uses the value functions in both stages. We give two algorithms ...
-
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 ...
-
2004-10-02BuchVariance reduction in sample approximations of stochastic programs This paper studies the use of randomized Quasi-Monte Carlo methods (RQMC) in sample approximations of stochastic programs. In high dimensional numerical integration, RQMC methods often substantially reduce the variance of ...
-
2004-09-13BuchOn deviation measures in stochastic integer programming We propose extensions of traditional expectation-based stochastic integer programs to mean-risk models. Risk is measured by expected deviations of suitable random variables from their means or from preselected targets. We ...
-
2004-09-13BuchConditional value-at-risk in stochastic programs with mixed-integer recourse In classical two-stage stochastic programming the expected value of the total costs is minimized. Recently, mean-risk models -- studied in mathematical finance for several decades -- have attracted attention in stochastic ...
-
2004-06-15BuchTreasury management model with foreign exchange exposure In this paper we formulate a model for foreign exchange exposure management and (international) cash management taking into consideration random fluctuations of exchange rates. A vector error correction model (VECM) is ...
-
2004-06-05BuchPolyhedral inclusion-exclusion Motivated by numerical computations to solve probabilistic constrained stochastic programming problems, we derive a new identity claiming that many terms are cancelled out in the inclusion-exclusion formula expressing the ...
-
2004-05-21BuchArbitrage pricing of American contingent claims in incomplete markets - a convex optimization approach Convex optimization provides a natural framework for pricing and hedging financial instruments in incomplete market models. Duality theory of convex optimization has been shown to yield elementary proofs of well-known ...
-
2004-05-17BuchA stochastic programming approach to resource-constrained assignment problems We address the resource-constrained generalizations of the assignment problem with uncertain resource capacities, where the resource capacities have an unknown distribution that can be sampled. We propose three stochastic ...
-
2004-05-17BuchAssessing policy quality in multi-stage stochastic programming Solving a multi-stage stochastic program with a large number of scenarios and a moderate-to-large number of stages can be computationally challenging. We develop two Monte Carlo-based methods that exploit special structures ...
-
2004-04-20BuchDecomposition-based interior point methods for two-stage stochastic convex quadratic programs with recourse Zhao [28] recently showed that the log barrier associated with the recourse function of two-stage stochastic linear programs behaves as a strongly self-concordant barrier and forms a self concordant family on the first ...
-
2004-04-16BuchMean-risk objectives in stochastic programming Traditional stochastic programming is risk neutral in the sense that it is concerned with the optimization of an expectation criterion. A common approach to addressing risk in decision making problems is to consider a ...
-
2004-03-25BuchConditional Risk Mappings We introduce an axiomatic definition of a conditional convex risk mapping and we derive its properties. In particular, we prove a representation theorem for conditional risk mappings in terms of conditional expectations. ...
-
2004-03-25BuchOptimization 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 ...
-
2004-03-01BuchConvexification of stochastic ordering We consider sets defined by the usual stochastic ordering relation and by the second order stochastic dominance relation. Under fairy general assumptions we prove that in the space of integrable random variables the closed ...
-
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 ...
-
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 ...
-
2004-02-19BuchThe million-variable "march" for stochastic combinatorial optimization Combinatorial optimization problems have applications in a variety of sciences and engineering. In the presence of data uncertainty, these problems lead to stochastic combinatorial optimization problems which result in ...
-
2004-02-10BuchEpi-convergent discretizations of multistage stochastic programs In many dynamic stochastic optimization problems in practice, the uncertain factors are best modeled as random variables with an infinite support. This results in infinite-dimensional optimization problems that can rarely ...
