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Abstract. Package carriers use sophisticated automated sorting facilities to efficiently process inbound packages and sort them to their down line destinations. During each of several daily processing windows, primary sorters [...]

Abstract. We consider two types of convex approximations of two-stage totally unimodular integer recourse models. Although worst-case error bounds are available for these approximations, their actual performance has not yet [...]

Oil and gas companies are drilling and developing fields in the Arctic Ocean, which is an environment with ice floes. These companies must protect their platforms from ice floe collisions. [...]

The infrastructure of the United States, and the world, is increasingly interconnected. The ongoing integration of systems--including transportation, energy, water, communications, finance and more--has been central to their growth in [...]

We take a novel approach to decision problems involving binary activity-selection decisions competing for scarce resources. The literature approaches such problems by forming an optimal portfolio of activities. However, often practitioners instead form a rank-ordered list of activities and select those with the highest priority. We account for both viewpoints. We rank activities considering both the uncertainty in the problem parameters and the optimal portfolio that will be obtained once the uncertainty is revealed. We use stochastic integer programming as a modeling framework, and we apply our approach to a facility location problem and a multidimensional knapsack problem. We develop two sets of cutting planes to improve computation. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2013.1865. Keywords: priority lists; activity-selection problem; stochastic programming; cutting planes History : Received December 20, 2011; accepted February 17, 2013, by Dimitris Bertsimas, optimization. Published online in Articles in Advance May 15, 2014., 1. Introduction Resource-constrained activity-selection problems (RCASPs) involve binary activity-selection decisions, which compete for scarce resources. The bulk of the current literature approaches RCASPs by forming an optimal portfolio of activities [...]

We consider a multiperiod system operation problem with two conflicting objectives, minimizing cost and risk. Risk sterns from uncertain disruptions to the system during operation. Whereas a general model would [...]

We develop a class of lower bounds on the expectation of a convex function. The bounds utilize the first two moments of the underlying random variable, whose support is contained [...]

We consider stochastic vehicle routing problems on a network with random travel and service times. A fleet of one or more vehicles is available to be routed through the network [...]