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Research on urban travel represents an important area in geography, transportation planning and urban studies. Compared to the traditional trip based approach, the activity based approach offers a better understanding of the motivations underlying travel, that is, activity participation. Urban activity-travel is complex as it takes place both in space and time. Building upon the time geography framework, this study provides new ways to characterize urban activity-travel and examine the association with accessibility. A new optimization model incorporating complex urban travel is also proposed for service provision planning. Activity space represents an important concept for understanding human activity-travel. The geometry based approaches widely used for delineating activity spaces are limited in fully characterizing real-world travel behavior. To address the issue, Chapter 2 proposes a new time geography based approach to more accurately portray urban activity spaces. The proposed approach takes into account the full complexity of real-world travel and underlying urban structures. Results of an empirical study are presented based on the 2008 Add-on National Household Travel Survey conducted in Tucson, Arizona. Activity spaces of 1,164 sample travelers are delineated and analyzed. Results show the effectiveness of the new approach in more realistically depicting urban activity-travel. Understanding the impact of the built environment on travel is important for formulating effective travel reduction policies. In Chapter 3, a study is presented to examine the relationship between accessibility to urban opportunities and urban travel. Activity spaces are drawn to characterize the spatial extent of activity-travel, and a new accessibility measure is introduced to account for the complexity of urban travel. An empirical study based on a travel survey dataset in Tucson, Arizona shows that improved accessibility is generally associated with reduced travel, but such an effect varies across different activity types. In addition, employment status and trip-chaining behavior can be used to explain the varying influences on the accessibility-travel relationship. In Chapter 4, a new multi-objective location model is developed with the goal of accessibility maximization. The model extends the classic p-median problem (PMP) to account for accessibility in a more realistic manner. Trip chaining and activity space are incorporated into the location model. In addition to fixed home locations, stops along chained trips are allowed for potential service site visits. The model is applied to locate service facilities in Tucson, AZ. Alternative versions of the objective function are solved exactly with the resulting sets of optimal facility locations displayed and analyzed. Decision makers are given flexibility to determine the relative importance for each of three sub-objective, based on the type of services being located, their preferences and practical needs.

During an emergency evacuation, most people will use their vehicles to evacuate. However, there is a group of people who do not have access to reliable transportation or for some reason cannot drive, even if they have their own automobiles - the carless. There are different groups of carless (disabled, medically homebound, poor or immigrant populations, etc.) who require different forms of transportation assistance during an emergency evacuation. In this study we focus on those carless who are physically intact and able to walk to a set of designated locations for transportation during an emergency, and we propose using public transit and school buses to evacuate this carless group. A model has been developed to accommodate the use of public transit and school buses to efficiently and effectively evacuate the carless. The model has two parts. Part 1 is a location problem which aims at congregating the carless at some specific locations called evacuation sites inside the affected area. To achieve this goal, the affected area is partitioned into zones and this congregating of the carless has been formulated as a Single Source Capacitated Facility Location Problem. Changes in the demand of the carless in zones over different periods of a day and over different days of the week have been considered and included in the model. A walking time constraint is explicitly considered in the model. A heuristic developed by Klincewicz and Luss (1986) has been used to solve this location model.Part 2 is a routing problem which aims at obtaining itineraries of buses to pick up the carless at evacuation sites and transport them to safe locations outside the affected area, such that the total number of carless evacuated with the given time limit is maximized. A Tabu search heuristic has been developed for solving the routing problem. Computational results show that the Tabu search heuristic efficiently and effectively solves the routing problem; in particular, the initial heuristic produces a high quality initial solution in very short time. This study has also made slight contribution to the development of the Tabu search technique.

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<p>Blood in Canada is donated by a volunteer base that is increasingly challenged, through a combination of demographic aging and immigration, to meet the needs of the health sector. Canadian Blood Services, the agency with the mandate to manage blood products in Canada with the exception of Quebec, is therefore actively involved in the development of programs to help increase the number of donors, to improve the retention of existing donors, and to increase the frequency of donation of repeat donors. An important factor that influences blood donation is the accessibility to clinics. Accessibility to clinics is determined by the location of clinics, the resources allocated to each clinic in terms of number of beds and hours of operation, and the distribution of the population in the areas serviced by the clinics. The objective of this research is to investigate, given a set of fixed sites for clinic locations and population characteristics, the potential for increasing the donor yield as a function of accessibility. A case study is presented of the Hamilton Census Metropolitan Area, in Canada. Using donor and clinic data provided by Canadian Blood Services, and census information, an objective function is derived by estimating a generalized linear model of donations. The objective function is maximized globally using Genetic Algorithm techniques, subject to total resources available for clinic operations. The results suggest that an optimized allocation of resources to clinic sites has the potential to increase the donor yield by approximately 50% of the current donor base.</p> / Master of Arts (MA)