A large number of problems in production planning and scheduling, location, transportation,
finance, and engineering design require that decisions be made in the presence of …

In this chapter, we will study algorithms for both two-stage as well as multi-stage stochastic
mixed-integer programs. We present stagewise (resource-directive) decomposition methods …

In thispaper we study a Monte Carlo simulation--based approach to stochastic discrete
optimization problems. The basic idea of such methods is that a random sample is …

We propose an approach to address data uncertainty for discrete optimization and network
flow problems that allows controlling the degree of conservatism of the solution, and is …

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 …

We develop a two-stage stochastic programming model for a humanitarian relief logistics
problem where decisions are made for pre-and post-disaster rescue centers, the amount of …

Over the last two decades, robust optimization has emerged as a computationally attractive
approach to formulate and solve single-stage decision problems affected by uncertainty …

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 …

provide models that could be used by do-it-yourselfers and also can be used toprovideunderstandingofthebackgroundiss…
job of working with the (proprietary) algorithms of the software vendors. In this book we …

This paper develops a solution strategy for two-stage stochastic programs with integer
recourse. The proposed methodology relies on approximating the underlying stochastic …