Samer M. Madanat
Samer Madanat is the Xenel Distinguished Professor of Engineering Emeritus, and former Director of the Institute of Transportation Studies at the University of California at Berkeley.
He received a B.Sc. in Civil Engineering from the University of Jordan in 1986, and a M.S and Ph.D. in Transportation Systems from MIT in 1988 and 1991 respectively.
His research and teaching interests are in the area of Transportation Infrastructure Management, with an emphasis on modeling facility performance and the development of optimal management policies under uncertainty.
In 2000, he received the Science and Technology grant from the University of California Office of the President, an award given annually to one faculty member in the UC system. From 2001 to 2011, he served as the Editor-in-Chief of the ASCE Journal of Infrastructure Systems. Several of his former students are faculty members at universities in the US and abroad.
Ph.D., Civil Engineering, Massachusetts Institute of Technology, 1991
M.S., Civil Engineering, Massachusetts Institute of Technology, 1988
B.S., Civil Engineering, University of Jordan, 1986
Samer Madanat's research group 2011-12
Samer Madanat's Research Group 2012-2013
Samer Madanat's Research Group 2014-15
Life-Cycle Maintenance Management for Bridge Networks under Reliability Considerations
With Xiaofei Hu, (PhD student)
The research addresses the problem of optimizing maintenance, rehabilitation and replacement (MR&R) decisions for deteriorating bridges in highway networks. Incorporating network topology increases the complexity of the maintenance optimization problem; the traditional MDP framework suffers from the curse of dimensionality. In the literature, numerical methods were implemented to solve bridge management problems in networks of small sizes.
In the first part of the research, we search for the optimal maintenance plan which ensures an adequate level of network reliability at the lowest possible life-cycle maintenance cost. We show that the network reliability function can be obtained directly from the minimal cut sets under reasonable approximations. Analytical and efficient approaches are developed for both decomposable and non-decomposable networks, and the framework is extended to networks with multiple origin-destination pairs. In the second part, we investigate large scale networks with the objective of minimizing the disruption to traffic caused by bridge failures. The critical step is to decompose the network-level problem into single facility problems. We theoretically prove the validity of this decomposition using a grid network model.
Decision support system for joint design, and strategic maintenance and rehabilitation planning for highway systems under multiple constraints
With Jinwoo Lee (PhD student)
The subject of this research is the joint optimization of pavement design and MR&R strategies for system-wide pavement infrastructure. We are currently focusing on the optimization of the structural number in design and the MR&R plan with multiple treatments such as maintenance and resurfacing for a single pavement to minimize its total life cycle costs, using a combination of analytical and numerical tools. We reduce the number of decision variables in mathematical programming by using calculus of variations and numerical methods. The next step will be to extend this method to a system of highway pavements under capital investment and maintenance constraints. The research results should be of use for developing countries in the process of expanding their highway networks in the face of multiple constraints.
Pavement Resurfacing Policy for Minimization of Lifecycle Costs and Greenhouse Gas Emissions: Network Level Analysis
With Darren Reger (PhD student) and Arpad Horvath
Traditionally, pavement management optimization has focused on minimizing user and agency costs. Previous research has expanded beyond minimization of life-cycle costs, to also include GHG emission, by solving the multi-criteria optimization problem with two objectives. Case studies were performed for an arterial and a major highway to highlight the contrast between policy decisions for various pavement and vehicle technologies. The current research aims to extend the multi-objective optimization methodology (with life-cycle costs and GHG emissions) to the management of an entire highway network in the presence of realistic constraints.
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