Presenter: Kaan Ozbay
Organization: New York University
INFRASTRUCTURE
Abstract:
Effective bridge management requires balancing long-term economic efficiency with resilience against risks posed by aging infrastructure and various hazards. Traditional life cycle cost analysis (LCCA) frameworks primarily focus on cost minimization, often underrepresenting risk and uncertainty factors that are critical for sustainable decision-making. To address this gap, our joint team from Rutgers’ RIME Lab and NYU C2SMART center, in collaboration with the NJDOT, developed a highly flexible and customizable Excel-Python integrated decision-support tool, ASSISTME-LCCA, that incorporates multi-objective optimization into the LCCA process. The framework enhances an existing Excel-based LCCA tool with Python-based automation and optimization capabilities, enabling the evaluation of bridge maintenance and rehabilitation strategies under budget constraints.
Using the Non-dominated Sorting Genetic Algorithm II (NSGA-II), the model generates Pareto-optimal solutions that jointly minimize life cycle costs and prioritize bridges with greater susceptibility to risks by maximizing risk scores, which can be customized through weighted parameters to emphasize different risk types. Additional objectives such as Annual Average Daily Traffic (AADT) can also be included in the optimization to align with agency priorities. A case study using representative bridge inventory and condition data demonstrates how the tool produces insights. Results highlight trade-offs between cost efficiency and risk mitigation, demonstrating the value of risk-integrated planning compared to cost-driven approaches. The approach offers a practical, data-driven methodology for allocating resources while ensuring long-term resilience. By equipping stakeholders with advanced optimization capabilities, this research supports the development of an improved transportation workforce prepared to address future challenges and contributing to resilient infrastructure management strategies.
Dr. Kaan Ozbay joined Civil and Urban Engineering at NYU Tandon School of Engineering as a tenured full Professor in 2013. He is the founding Director of the C2SMART Center at NYU Tandon School of Engineering which was established in 2017. Prior to that, Professor Ozbay was a tenured full Professor at Rutgers University’s Department of Civil and Environmental Engineering where he joined as an Assistant Professor in July 1996. In 2008, he was a visiting scholar at the Operations Research and Financial Engineering (ORFE) Department at, Princeton University. Dr. Ozbay is the recipient of several awards including the prestigious National Science Foundation (NSF) CAREER award, IBM faculty award, INFORMS Franz Edelman Finalist Award, in addition to several best paper and excellence in research awards. His research interests in transportation cover a wide range of topics including data-driven AI/ML applications in smart cities, development and calibration of large-scale complex transportation simulation models. He has co-authored 4 books and published approximately 500 refereed papers in scholarly journals and conference proceedings. Prof. Ozbay is also an Associate Editor of the ITS journal and serves as the Associate Editor of Networks and Spatial Economic journal and Transportmetrica B: Transportation Dynamics journal. Since 1994, Dr. Ozbay, has been the Principal Investigator and Co-Principal Investigator of 125 research projects funded at a level of more than $35M by USDOT, National Science Foundation, NCHRP, NJDOT, NY State DOT, NYC DOT, New Jersey Highway Authority, FHWA, VDOT, Dept. of Homeland Security, among others.
Presentation Slides:
To be added.