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In the design of tall buildings, the lateral system that resists wind and seismic loading usually dominates the structural engineering effort; therefore, optimal lateral system design is important for material efficiency. ...

Automobile growth has created severe problems such as traffic congestion, air pollution, and carbon emission worldwide. To address these problems, Chinese local governments implemented a series of automobile regulations ...

Calibration of a DTA model is needed before applying it in a real-world road network. Calibration is often formulated as an optimization problem. This problem is difficult because of the large number of parameters, ...

High-frequency rail transit systems such as subways play a key role in urban transportation; as such, the choices made in the design, implementation, and operation of rail networks are important. To fully understand the ...

Service reliability is a major concern for public transportation agencies. Transit services experience natural variability in scheduled service, due to factors such as traffic congestion, irregular demand, multi-route and ...

Dar es Salaam is one of numerous large cities in the developing countries facing tremendous development challenges: growing population, rapid urbanization and motorization, sprawled informal settlements, problematic informal ...

This thesis focuses on the evolution of U.S. airline business models from 2006-2015, and the impacts of these changes on other stakeholders in the U.S. air transportation system. The U.S. airline industry has been affected ...

The Resource Allocation Game we examined in this work is a strategic interaction where a principal distribute an infinitely divisible good among different agents based on their specific valuations of said good. The ...

This thesis studies routing in a general single o-d network and information structure induced by any two heterogeneous information systems. To model the asymmetric information environment, we formulate a Bayesian congestion ...

The thesis presents the work with a hotel company, as an example of how machine learning techniques can be applied to improve demand predictions and help a hotel property to make better decisions on its pricing and capacity ...