This Computational Operations Research (COR) program is strongly interdisciplinary, it is offered by the Departments of Mathematics, Computer Science, Applied Science, and Public Policy. We offer the following degrees:, A Master of Science (M.S.) in Computer Science with specialization in COR., A concurrent Master of Science (M.S.) and Master of Public Policy (M.P.P.). Students can simultaneously earn their M.S. and M.P.P. in three years., A Doctor of Philosophy (Ph.D.) in either Applied Science or Computer Science specializing in COR. The Ph.D. program prepares students for research careers in either academia or industry. The program generally can be completed in five years or less of graduate study. By the time they finish the coursework required to satisfy candidacy requirements (in four semesters or less), students are expected to have identified a principal research advisor to direct their dissertation. Graduation requires the successful defense of a dissertation based on original research that contributes to the body of knowledge in the student's chosen area of research. Operations research stems from a study of military operations conducted during World War II that sought optimal ways to allocate scarce resources. Today, practitioners model and analyze the behavior of real world systems using advanced analytical and computational techniques to make informed decisions in areas such as healthcare and manufacturing, in service organizations, the military, and government. Sample applications include airline crew scheduling, actuator placement in flexible space structures, efficient image reconstruction, allocation of spare parts, job shop scheduling, reliability, and performance analysis., Operations research has been taught at William & Mary for over 30 years and the current Computational Operations Research curriculum has been in place since 1999. The COR faculty consists of professors from Applied Science, Computer Science, Public Policy, and Mathematics, and includes experts in convex programming, discrete optimization, nonlinear programming, simulation, statistics, and business analytics.