Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 1990. / Thesis Advisor(s): Melich, Michael ; Boger, Dan C. Second Reader: Rosenthal, Richard E. "September 1990." Description based on title screen viewed on December 16, 2009. DTIC Descriptor(s): Cost models, recovery, models, low costs, cost estimates, costs, sea launched, logistics, fuel tanks, space transportation, space missions, rocket fuels, position(location), fuels. DTIC Identifier(s): Launch vehicles, cost analysis, sea launch and recovery space transportation systems, theses. Author(s) subject terms: Optimization. Also available in print.

Thesis (M.Sc.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 64-65) Also available in print.

<p> This research studied the behavior of several controllable variables that affect the fuel efficiency of trucks. Re-routing is the process of modifying the parameters of the routes for a set of trips to optimize fuel consumption and also to increase customer satisfaction through efficient deliveries. This is an important process undertaken by a food distribution company to modify the trips to adapt to the immediate necessities. A predictive model was developed to calculate the change in Miles per Gallon (MPG) whenever a re-route is performed on a region of a particular distribution area. The data that was used, was from the Dallas center which is one of the distribution centers owned by the company. A consistent model that could provide relatively accurate predictions across five distribution centers had to be developed. It was found that the model built using the data from the Corporate center was the most consistent one. The timeline of the data used to build the model was from May 2013 through December 2013. The predictive model provided predictions of which about 88% of the data that was used, was within the 0-10% error group. This was an improvement on the lesser 43% obtained for the linear regression and K-means clustering models. The model was also validated on the data for January 2014 through the first two weeks of March 2014 and it provided predictions of which about 81% of the data was within the 0-10 % error group. The average overall error was around 10%, which was the least for the approaches explored in this research. Weight, stop count and stop time were identified as the most significant factors which influence the fuel efficiency of the trucks. Further, neural network architecture was built to improve the predictions of the MPG. The model can be used to predict the average change in MPG for a set of trips whenever a re-route is performed. Since the aim of re-routing is to reduce the miles and trips; extra load will be added to the remaining trips. Although, the MPG would decrease because of this extra load, it would be offset by the savings due to the drop in miles and trips. The net savings in the fuel can now be translated into the amount of money saved.</p>

Thesis (M.A.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 138-141) Also available in print.

Thesis (Ph. D.)--University of Texas at Austin, 2005. / Vita. Includes bibliographical references.

<p> The future success of traffic management is contingent upon the advancement of information logistic systems. The ability to provide accurate, valid, and timely information is critical to the effectiveness of an intelligent transportation system&rsquo;s ability to improve public safety and economic growth. Traffic Operation Centers (TOC) receive and disseminate information with various actors in real-time and near real-time environments. Using the traffic incident management business process for a Traffic Operation Center, this research explores the effects of designing a traffic management system in context to the business process. Two system designs for a TOC are compared using the system architecture maps and incident duration time stamps captured during the use of each system. The results show the impact of using process-oriented information logistics (POIL) during the design phase when developing traffic management systems. </p><p>

Roads deteriorate at different rates from weathering and use. Hence, transportation agencies must assess the ride quality of a facility regularly to determine its maintenance needs. Existing models to characterize ride quality produce the International Roughness Index (IRI), the prevailing summary of roughness. Nearly all state agencies use Inertial Profilers to produce the IRI. Such heavily instrumented vehicles require trained personnel for their operation and data interpretation. Resource constraints prevent the scaling of these existing methods beyond 4% of the network. This dissertation developed an alternative method to characterize ride quality that uses regular passenger vehicles. Smartphones or connected vehicles provide the onboard sensor data needed to enable the new technique. The new method provides a single index summary of ride quality for all paved and unpaved roads. The new index is directly proportional to the IRI. A new transform integrates sensor data streams from connected vehicles to produce a linear energy density representation of roughness. The ensemble average of indices from different speed ranges converges to a repeatable characterization of roughness. The currently used IRI is undefined at speeds other than 80 km/h. This constraint mischaracterizes roughness experienced at other speeds. The newly proposed transform integrates the average roughness indices from all speed ranges to produce a speed-independent characterization of ride quality. This property avoids spatial wavelength bias, which is a critical deficiency of the IRI. The new method leverages the emergence of connected vehicles to provide continuous characterizations of ride quality for the entire roadway network. This dissertation derived precision bounds of deterioration forecasting for models that could utilize the new index. The results demonstrated continuous performance improvements with additional vehicle participation. With practical traversal volumes, the achievable precision of forecast is within a few days. This work also quantified capabilities of the new transform to localize roadway anomalies that could pose travel hazards. The methods included derivations of the best sensor settings to achieve the desired performances. Several case studies validated the findings. These new techniques have the potential to save agencies millions of dollars annually by enabling predictive maintenance practices for all roadways, worldwide. / Mountain Plains Consortium (MPC)

Thesis (Ph.D.)--University of Nebraska-Lincoln, 2009. / Title from title screen (site viewed January 5, 2010). PDF text: xi, 178 p. : ill. ; 2 Mb. UMI publication number: AAT 3360157. Includes bibliographical references. Also available in microfilm and microfiche formats.

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

Thesis (M.S.)--Ohio State University, 2009. / Title from first page of PDF file. Includes vita. Includes bibliographical references (p. 84-86).