Currently, asphalt mixtures are design using volumetric concepts to determine optimum asphalt content levels with no means of verifying mixture performance prior to field production and placement. A new design methodology called Balanced Mixture Design (BMD) promotes the use of evaluating and design asphalt mixture using rutting and fatigue cracking methods and criteria to achieve an optimum asphalt content that will result in an asphalt mixture performing well in rutting and fatigue cracking scenarios – thereby “balancing” the asphalt mixture performance.

While Manhattan’s streets may be the most congested—and carbon-emitting—in the country, the subway system that runs beneath them offers an inspiring example of how efficiently—and with what minimal emissions of greenhouse gases—passengers can be transported. Although the collection and transport of municipal solid wastes produces only a fraction of the congestion and emissions on Manhattan’s surface, in absolute terms the hundreds of thousands of annual truck miles these wastes cause are nonetheless quite significant.

The environmental and economic impacts of New York State’s waste-management system could be dramatically reduced by (a) decreasing the number of truck miles required to collect waste and (b) decreasing the demand for long-distance transport to remote disposal facilities.

The objective of this exploratory research is to investigate the potential of dynamic pricing to avoid unbalanced inventory in bicycle sharing systems, and therefore the needs for manual rebalancing of bicycles by truck. The proposed idea of dynamic pricing has been not used in the current practice, and the idea’s potential is unknown to the service providers. In this exploratory research, I will investigate the idea’s potential to eliminate manual rebalancing using an optimization model with demand learning process. The model will be validated with real data.