This thesis has focused on an aircraft schedule and network design problem that involves multiple types of aircraft and flight service. First, this thesis expands a business model for integrating on-demand flight services with the traditional scheduled flight services. Then, this thesis proposes a three-step approach to the design of aircraft schedules and networks from scratch. After developing models in the three steps and creating large-scale instances of these models, this dissertation develops iterative algorithms and subproblem approaches to solving these instances, and it presents computational results of these large-scale instances. To validate the models and solution algorithms developed, this thesis compares the daily flight schedules that it designed with the schedules of the existing airlines. In addition, it discusses the implication of using new aircraft in the future flight schedules. Finally, future research in three areas--model, computational method, and simulation for validation--is proposed.

Local agencies must comply with environmental justice regulation and as such, it is important that they possess practical tools to identify target populations and assess impacts of projects, programs, and policies on these populations. These tools are not readily available or fully developed to evaluate impacts on a regional level, especially when the impacts are benefits rather than burdens. This issue comes into play when accessibility is assessed. This analysis measures accessibility for an environmental justice evaluation using spatial statistical clusters and cumulative opportunity. It shows that the majority of schools, libraries and local transit lines are within areas with high concentrations of target populations, however, park space is limited in these areas. Alternative approaches for environmental justice assessments of regional outcomes such as accessibility provide opportunities for MPOs to gain a greater understanding of the regional impacts of transportation improvements as well as more accurately comply with the spirit of environmental justice regulations.

published_or_final_version / abstract / Civil Engineering / Master / Master of Philosophy

Traditionally, the resilient modulus values obtained from repeated unconfined or triaxial compression tests are used as the elastic modulus of granular layers in structural analysis of flexible pavements. Sometimes the resilient modulus of granular materials are estimated from known California bearing ratios (CBR) or stabilometer resistance (R) values by simple regression equations. On the other hand, it is well known that stress-strain relation for unbound granular materials is nonlinear and the resilient modulus increases with the increase in stress intensity. There exist several models for stress dependent nonlinear behavior of unbound granular materials. These models are incorporated into elastic layered analysis by applying a method of successive approximations in order to get more realistic pavement responses. Kenlayer is a popular computer program incorporating nonlinear behavior of granular materials in elastic layered system. In this computer program, the resilient modulus of granular materials are varied in vertical direction only, without considering variations in radial direction. In this study, simplest model namely K-Q model for stress dependency of granular layer is applied in structural analysis of flexible pavements. This model is adopted for use in finite element analysis carried by SAP90 software. Analyses are performed over 24 different three-layered pavement structures by changing asphaltic concrete modulus values, granular base thicknesses, base materials and subgrade modulus values. Critical pavement responses namely tensile strains at the bottom of asphaltic surface layers and compressive strains on top of subgrade are obtained for each pavement by linear layered elastic, nonlinear layered elastic and nonlinear finite element solutions. The pavement lives are calculated by using selected performance equations. The results of layered systems and finite element solutions are compared. It is observed that, results obtained from finite element model and linear elastic solutions differ considerably.

In this thesis the capacitated vehicle routing problem with time windows (VRPTW) is studied, where the objective is to serve a set of geographically dispersed customers with known demands and predefined time windows at the minimum cost. It is hard to find an optimal solution for the VRPTW even if the problem size is small. Therefore, many heuristic methods are developed to obtain near optimal solutions. In this study a local search algorithm is proposed for solving the VRPTW, which consist of route construction and route improvement phases. Computational experiments are conducted with Solomon (1987)&rsquo / s and Homberger and Gehring (1999)&rsquo / s problem sets in order to test the performance of the proposed algorithm. From the computational results encouraging results are obtained in terms of solution quality.

Thesis (Ph. D.)--Rutgers University, 2007. / "Graduate Program in Civil and Environmental Engineering." Includes bibliographical references.

Thesis (M.S.)--Rochester Institute of Technology, 2008. / Typescript. Includes bibliographical references (leaves 62-63).

Dynamic signal control provides significant benefits in terms of travel time, travel time reliability, and other performance measures of transportation systems. The goal of this research is to develop and evaluate a methodology to support the planning for operations of dynamic signal control utilizing a multi-resolution analysis approach. The multi-resolution analysis modeling combines analysis, modeling, and simulation (AMS) tools to support the assessment of the impacts of dynamic traffic signal control. Dynamic signal control strategies are effective in relieving congestions during non-typical days, such as those with high demands, incidents with different attributes, and adverse weather conditions. This research recognizes the need to model the impacts of dynamic signal controls for different days representing, different demand and incident levels. Methods are identified to calibrate the utilized tools for the patterns during different days based on demands and incident conditions utilizing combinations of real-world data with different levels of details. A significant challenge addressed in this study is to ensure that the mesoscopic simulation-based dynamic traffic assignment (DTA) models produces turning movement volumes at signalized intersections with sufficient accuracy for the purpose of the analysis. Although, an important aspect when modeling incident responsive signal control is to determine the capacity impacts of incidents considering the interaction between the drop in capacity below demands at the midblock urban street segment location and the upstream and downstream signalized intersection operations. A new model is developed to estimate the drop in capacity at the incident location by considering the downstream signal control queue spillback effects. A second model is developed to estimate the reduction in the upstream intersection capacity due to the drop in capacity at the midblock incident location as estimated by the first model. These developed models are used as part of a mesoscopic simulation-based DTA modeling to set the capacity during incident conditions, when such modeling is used to estimate the diversion during incidents. To supplement the DTA-based analysis, regression models are developed to estimate the diversion rate due to urban street incidents based on real-world data. These regression models are combined with the DTA model to estimate the volume at the incident location and alternative routes. The volumes with different demands and incident levels, resulting from DTA modeling are imported to a microscopic simulation model for more detailed analysis of dynamic signal control. The microscopic model shows that the implementation of special signal plans during incidents and different demand levels can improve mobility measures.

M.Ing. (Transportation) / This reseach focused on a quick response transportation planning software package called QRS II which was developed by A J Horowitz at the Centre for Urban Transportation Studies, University of Wisconsin, United states of America. The programme achieves its quick response by incorporating, inter alia, a large number of default parameters within its formulation. Several of these parameters define the typical travel characteristics of the population within a study area and as such, suggest a particular socioeconomic, political, cultural and behavioral profile as existing in that area. These typical conditions may be representative of the behavior in many areas in the United States but may not adequately reflect conditions beyond that. This study has set out to determine whether the default parameters used in QRS II are different to those that would be appropriate in Black towns in areas such as the East Rand Metropolitan Transport Area (ORMET) in South Africa. Local parameter values were identified and compared with the default values in QRS II. It was found that these values were significantly different. More research is required before QRS II can be considered fully adapted to conditions in Black urban areas within a Metropolitan area such as ORMET. However, the new values suggested in this study will go a long way to improving the appropriateness of QRS II applications in South Africa.

Today’s logistics practices are moving from inventory-based push supply chains to replenishment-based pull supply chains, leading to a lower and less centralized inventory, smaller shipment sizes, and more just-in-time deliveries. As a result, industries are now demanding greater reliability in freight transportation. Delays and uncertainty in freight transportation translate directly into additional inventory, higher manufacturing costs, less economic competitiveness for businesses, and higher costs of goods that are being passed on to the consumers. Given the growing demand in freight transportation, the emerging needs to better understand freight behavior for better policy and investment decisions, and the increasing role of reliability in freight transportation, this research aims at providing a) better understanding of how the freight system users value travel time reliability in their transportation decisions, and b) advanced methods in quantifying the user’s willingness to pay for the improvement of transportation related attributes, particularly travel time reliability. To understand how the freight industry values travel time reliability in their transportation decisions, and particularly the presence of user heterogeneity, this research designed and conducted a stated preference (SP) survey for freight users in road transportation. Based on the feedback received during the pilot stage, reliability was measured as the standard deviation of travel time and presented as a frequency of on-time and late delivery in the choice scenarios. The survey collected 1,226 responses from 159 firms in Florida between January and May 2016 via online and paper methods. Various modeling approaches were explored to estimate the willingness to pay (WTP) measures among freight users, including multinomial logit (MNL) and mixed logit model. Market segmentation and interaction modeling techniques were employed to investigate preference variations among user groups, commodity groups, product type, and various other shipment characteristics, including shipping distance and weight. In general, across all groups in the sample, values of $37.00 per shipment-hour ($1.53 per ton-hour) for travel time savings and $55.00 per shipment-hour ($3.81 per ton- hour) for improvements of reliability were found in this research. Furthermore, while investigating the effects of shipping characteristics on the user’s preference in WTP, the results suggested that shipping distance and weight were the two most important variables. The results of the study help advance the understanding of the impact of the performance of transportation systems on freight transportation, which will lead to policy and investment decisions that better serve the needs of the freight community.