Speakers
Michael P. Johnson, PhD
Dr. Michael P. Johnson is Associate Professor of Management Science and Urban Affairs (untenured) in the H. John Heinz III School of Public Policy and Management, Carnegie Mellon University, Pittsburgh, PA. Dr. Johnson received his PhD in operations research from Northwestern University in 1997, and his B.S. from Morehouse College in 1987.
Dr. Johnson's research interests include public-sector facility location, service delivery and decision support, with a primary focus on affordable housing and community development, and broader applications to disadvantaged and/or vulnerable populations. His primary mission is to develop models and applications that enable public organizations to develop and analyze policies and planning strategies that jointly optimize economic efficiency, beneficial population outcomes and social equity.
Dr. Johnson has taught courses in decision support systems, operations research, cost-benefit analysis and management information systems, and has supervised numerous capstone project courses in two Heinz School master's degree programs.
His work has appeared in or is in press at a variety of journals, including Annals of Operations Research, Decision Support Systems, Environment and Planning A, Environment and Planning B, Housing Studies, Journal of Economic Behavior and Organization, Journal of Geographic Systems, Journal of Housing Research, Location Science, Management Science, Papers of the Regional Science Association, and Socio-Economic Planning Sciences. His work has also appeared or is in press in refereed volumes including Proceedings of the 48th Hawaii International Conference on System Sciences, Encyclopedia of Gender and Information Technology, Encyclopedia of Life Support Systems (EOLSS): Advanced Geographic Information Systems and Sixth Industrial Engineering Research Conference Proceedings.
Dr. Johnson is a member of a number of professional societies, including the Institute for Operations Research and the Management Sciences, the Regional Science Association and the National Economic Association. He is a current National Science Foundation CAREER Postdoctoral fellow, and has previously received postdoctoral fellowships from the U.S. Department of Housing and Urban Development Urban Scholars program and the National Consortium on Violence Research.
Dr. Johnson has also performed a variety of community service and outreach activities, including assisting the Pittsburgh Public Schools in designing resource realignment strategies, directing a community planning process for the Highland Park neighborhood in Pittsburgh and serving on the advisory board for an information technology-based social entrepreneurship initiative.
Dr. Johnson was born in Chicago, Illinois. He is married, with two sons, aged nine and three. Leisure activities include reading, listening to jazz music and playing with his children.
"Mathematical Models for Post-Disaster Reconstruction Planning in Urban Areas"
In the aftermath of a natural disaster, urban planners need to decide how neighborhoods should be restored under limited resources. An ill-planned reconstruction strategy and implementation may result in socially inefficient land uses and subject neighborhoods to excessive future risk of disaster damage. In this study, we develop prescriptive mathematical models for the design of redevelopment strategies that maximize social welfare. We define redevelopment strategies for neighborhoods damaged by natural disasters as decisions regarding whether to rebuild a set of neighborhood for human habitation or not. The alternative to human habitation is for the land to be uninhabitated, and perhaps improved somewhat for recreation or environmental safety purposes. We construct and evaluate the neighborhood development model to maximize the total viability (social net benefit) of neighborhoods through assignment of land uses under a number of constraints that include budget, contiguity and spatial orientation. We develop alternative solution strategies and identify policy implications of the math program as applied to stylized model instances.