Data-Driven Operations Research Analyses in the Public Sector

2013 INFORMS Annual Meeting Minneapolis
Plenaries and Keynotes
Omega Rho Distinguished Lecture
Presented by Lawrence M. Wein, Stanford University
Lawrence M. Wein describes several recent projects in the public sector, including screening and treatment for childhood obesity, allocating blood for transfusions, optimizing ballistic imaging performance using spatiotemporal crime data, allocating ready-to-use food to children in developing countries, and optimizing the biometric aspects of India's universal identification (UIDAI) program. Each project started with a large longitudinal data set that guided the mathematical modeling, and resulted in a recommended policy that outperforms the current policy. For each project, he briefly describes the problem motivation, the data set, the mathematical model (which was embedded into an optimization problem), the statistical analysis required to calibrate the model, the numerical results from solving the optimization problem, and the policy implications.

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