Date of Award


Document Type


Degree Name

Master of Science in Operations Research


Department of Operational Sciences

First Advisor

Raymond R. Hill, PhD.


This paper compares linear programming and stable marriage approaches to the assignment problem under conditions of uncertainty. Robust solutions should exhibit reduced variability in the presence of one or more additional constraints. Several variations of each approach are compared with respect to solution quality, as measured by the overall social welfare among Officers and Assignments, and robustness as measured by the number of changes after a number of randomized perturbations. We examine the contrasts between these methods in the context of assigning Army Officers among a set of identified assignments. Additional constraints are modeled after realistic scenarios faced by Army assignment managers, with parameters randomized. The Pareto efficient approaches, relative to these measures of quality and robustness, are identified and subjected to a regression analysis. The coefficients of these models provide insight into the impact the different scenarios under study, as well as inform any trade-off decisions between Pareto-optimal approaches.

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