The University of Central Florida, with an enrollment of approximately 16,000 students, is being faced with parking, traffic and transportation problems. The University of Central Florida (UCF) is a commuter campus, with over 90% of the students arriving by automobile. Parking spaces cost over $800/space, and funding to build new spaces is scarce. Existing lots on the perimeter of the UCF campus offer a potential advantage to park and ride services or a shuttle serve around UCF. Research conducted for this paper evaluated the usage of a shuttle bus system around the UCF campus. The primary purpose of the shuttle is to move people around the campus, similar to the shuttle used by Disney. This is benefit primarily to the users, but it is also an asset to the whole campus, especially since it increased the general mobility of the University population and its accessibility to various locations and activities. The size of a shuttle travel area around the campus, routes that would serve all major areas of the campus and cost of the shuttle bus are the major points evaluated in the research report. The methodology included in this study references the Urban Transportation Planning Process (UTPP), which consists of four sub-models: (1) trip generation, (2) trip distribution, (3) modal split and (4) traffic assignment.

published_or_final_version / Transport Policy and Planning / Master / Master of Arts

Thesis (Ph.D.)(Industrial Engineering)--University of Pretoria, 2006. / Includes summary. Includes bibliographical references. Available on the Internet via the World Wide Web.

published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

South Africa provides a fascinating interface between the developed and the developing world and poses a multitude of opportunities for enhancing the sustainable development of local cities. The concept of City Logistics is concerned with the mobility of cities, and entails the process of optimizing urban logistics activities by considering the social, environmental, economic, financial, and energy impacts of urban freight movement. Vehicle routing and scheduling has the potential to address a number of these key focus areas. Applying optimization to vehicle routing and scheduling results in a reduced number of trips, better fleet utilization, and lower maintenance costs; thereby improving the financial situation of the fleet owner. Improved fleet utilization could have a positive environmental impact, while also improving the mobility of the city as a whole. Energy utilization is improved while customer satisfaction could also increase through on-time deliveries and reliability. The Vehicle Routing Problem (VRP) is a well-researched problem in Operations Research literature. The main objective of this type of problem is to minimize an objective function, typically distribution cost for individual carriers. The area of application is wide, and specific variants of the VRP transform the basic problem to conform to application specific requirements. It is the view of this dissertation that the various VRP variants have been researched in isolation, with little effort to integrate various problem variants into an instance that is more appropriate to the South African particularity with regards to logistics and vehicle routing. Finding a feasible, and integrated initial solution to a hard problem is the first step in addressing the scheduling issue. This dissertation attempts to integrate three specific variants: multiple time windows, a heterogeneous fleet, and double scheduling. As the problem is burdened with the added constraints, the computational effort required to find a solution increases. The dissertation therefore also contributes to reducing the computational burden by proposing a concept referred to as time window compatibility to intelligently evaluate the insertion of customers on positions within routes. The initial solution algorithm presented proved feasible for the integration of the variants, while the time window compatibility decreased the computational burden by 25%, and as much as 80% for specific customer configurations, when using benchmark data sets from literature. The dissertation also improved the quality of the initial solution, for example total distance traveled, by 13%. Finding an initial solution is the first step in solving vehicle routing problems. The second step is to improve the initial solution iteratively through an improvement heuristic in an attempt to find a global optimum. Although the improvement heuristic falls outside the scope of this dissertation, improvement of the initial solution has a significant impact on the quality of improvement heuristics, and is therefore a valuable contribution. / Dissertation (MEng)--University of Pretoria, 2007. / Industrial and Systems Engineering / MEng / Unrestricted