Markov Decision Process Design: A Framework for Integrating Strategic and Operational Decisions

We consider the problem of optimally designing a system for repeated use under uncertainty. We develop a modeling framework that integrates design and operational phases, which are represented by a mixed-integer program and discounted-cost infinite-horizon Markov decision processes, respectively. We seek to simultaneously minimize the design costs and the subsequent expected operational costs. This problem … Read more

Characterizing Rational Transplant Program Response to Outcome-Based Regulation

Organ transplantation is an increasingly common therapy for many types of end-stage organ failure, including lungs, hearts, kidneys and livers. The past twenty years have seen increased scrutiny of post-transplant outcomes in the United States, in order to ensure the efficient utilization of the scarce organ supply. Under regulations by the Organ Procurement Transplantation Network … Read more

Relaxations and Duality for Multiobjective Integer Programming

Multiobjective integer programs (MOIPs) simultaneously optimize multiple objective functions over a set of linear constraints and integer variables. In this paper, we present continuous, convex hull and Lagrangian relaxations for MOIPs and examine the relationship among them. The convex hull relaxation is tight at supported solutions, i.e., those that can be derived via a weighted-sum … Read more