We present an algorithm for solving stochastic integer programming problems with recourse, based on a dual decomposition scheme and La-grangian relaxation. The approach can be applied to multi-stage problems with mixed-integer variables in each time stage. Numerical experience is presented for some two-stage test problems.

We present an algorithm for solving stochastic integer programming problems with recourse, based on a dual decomposition scheme and Lagrangian relaxation. The approach can be applied to multi-stage problems with mixed-integer variables in each time stage. Numerical experience is presented for some two-stage test problems.

In this paper, we considered a Stochastic Interval-Valued Linear Fractional Programming problem(SIVLFP). In this problem, the coefficients and scalars in the objective function are fractional-interval, and technological coefficients and the quantities on the right side of the constraints were random variables with the specific distribution. Here we changed a Stochastic Interval-Valued Fractiona...

A dynamic (multi-stage) stochastic programming model for the weekly cost-optimal generation of electric power in a hydro-thermal generation system under uncertain demand (or load) is developed. The model involves a large number of mixed-integer (stochastic) decision variables and constraints linking time periods and operating power units. A stochastic Lagrangian relaxation scheme is designed by...

This paper presents a branch-and-cut method for two-stage stochastic mixed-integer programming (SMIP) problems with continuous firststage variables. This method is derived based on disjunctive decomposition (D) for SMIP, an approach in which disjunctive programming is used to derive valid inequalities for SMIP. The novelty of the proposed method derives from branching on the first-stage continu...

We present a study of the two-stage stochastic view selection problem in database management systems. The objective is to minimize processing times of the given queries subject to a storage limit. We assume that the queries are given in two or more workloads. We propose a two-stage stochastic programming (SP) model for this problem and study the structure and properties of its extensive form, w...

This paper presents a decision making approach for mid-term scheduling of large industrial consumers based on the recently introduced class of Stochastic Dominance (SD)- constrained stochastic programming. In this study, the electricity price in the pool as well as the rate of availability (unavailability) of the generating unit (forced outage rate) is considered as uncertain parameters. Th...

Optimization under Uncertainty Optimization under Uncertainty: An Overview Urmila Diwekar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Two-Stage Stochastic Linear Programming: A Tutorial Vicente Rico-Ramirez . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Combinatorial Optimization under Uncertainty Ki-Joo Kim . . . . . . . . . . . . . . . . . . . . . . . . . . ...

This paper considers the mobile facility routing and scheduling problem with stochastic demand (MFRSPSD). The MFRSPSD simultaneously determines the route and schedule of a fleet of mobile facilities which serve customers with uncertain demand to minimize the total cost generated during the planning horizon. The problem is formulated as a two-stage stochastic programming model, in which the firs...