The Benders decomposition algorithm has been successfully applied to a wide range of
difficult optimization problems. This paper presents a state-of-the-art survey of this algorithm …

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 …

The aim of stochastic programming is to find optimal decisions in problems which involve
uncertain data. This field is currently developing rapidly with contributions from many …

A bi-level, three-stage Stochastic Mathematical Program with Equilibrium Constraints
(SMPEC) is proposed for quantifying and optimizing travel time resilience in roadway …

We address a pre-disaster planning problem that seeks to strengthen a highway network
whose links are subject to random failures due to a disaster. Each link may be either …

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 …

In this paper, we consider a linear two-stage robust optimization model with a mixed integer
recourse problem. Currently, this type of two-stage robust optimization model does not have …

This paper presents a two-stage stochastic programming model used to design and manage
biodiesel supply chains. This is a mixed-integer linear program and an extension of the …

We study the problem of integrated staffing and scheduling under demand uncertainty. This
problem is formulated as a two-stage stochastic integer program with mixed-integer …

Supplier selection is an important strategic supply chain design decision. Incorporating
uncertainty of demand and supplier capacity into the optimization model results in a robust …