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.

Efficient and reliable public transport systems are fundamental in promoting green growth developments in metropolitan areas. A large range of Advanced Public Transport Systems (APTS) facilitates the design of real-time operations and demand management. The analysis of transit performance requires a dynamic tool that will enable to emulate the dynamic loading of travelers and their interaction with the transit system. BusMezzo, a dynamic transit operations and assignment model was developed to enable the analysis and evaluation of transit performance and level of service under various system conditions and APTS. The model represents the interactions between traffic dynamics, transit operations and traveler decisions. The model was implemented within a mesoscopic traffic simulation model. The different sources of transit operations uncertainty including traffic conditions, vehicle capacities, dwell times, vehicle schedules and service disruptions are modeled explicitly. The dynamic path choice model in BusMezzo considers each traveler as an adaptive decision maker. Travelers’ progress in the transit system consists of successive decisions that are defined by the need to choose the next path element. The evaluations are based on the respective path alternatives and their anticipated downstream attributes. Travel decisions are modeled within the framework of discrete random utility models. A non-compensatory choice-set generation model and the path utility function were estimated based on a web-based survey. BusMezzo enables the analysis and evaluation of proactive control strategies and the impacts of real-time information provision. Several experiments were conducted to analyze transit performance from travelers, operator and drivers perspectives under various holding strategies. This analysis has facilitated the design of a field trial of the most promising strategy. Furthermore, a case study on real-time traveler information systems regarding the next vehicle arrival time investigated the impacts of various levels of coverage and comprehensiveness. As passengers are more informed, passenger loads are subject to more fluctuation due to the traveler adaptations. / QC 20111201

<p>New technologies such as electric vehicles, Autonomous vehicles and transportation platforms are changing the way humanity move in a dramatic way and cities around the world need to adjust to this rapid change brought by technology. One of the aspects more challenging for urban planners is the parking problem as the new increase or desire for these private technologies may increase traffic congestion and change the parking requirements across the city. For example, Electric vehicles will need parking places for both parking and charging and Autonomous vehicles could increase the congestion by making longer trips in order to search better parking alternatives. Thus, it becomes essential to have clear, precise and practical models for transportation engineers in order to better represent present and future scenarios including normal vehicles, autonomous vehicles and electric vehicles in the context of parking and traffic alike. Classical network model such as traffic assignment have been frequently used for this purpose although they do not take into account essential aspects of parking such as fixed capacities, variety of users and autonomous vehicles. In this work a new methodology for modelling parking for multi class traffic assignment is proposed including autonomous vehicles and hard capacity constraints. The proposed model is presented in the classical Cournot Game formulation based on path flows and in a new link-node formulation which states the traffic assignment problem in terms of link flows instead of path flows. This proposed model allows for the creation of a new algorithm which is more flexible to model requirements such as linear constrains among different players flows and take advantage of fast convergence of Linear programs in the literature and in practice. Also, this link node formulation is used to redefine the network capacity problem as a linear program making it more tractable and easier to calculate. Numerical examples are presented across this work to better exemplify its implications and characteristics. The present work will allow planners to have a clear methodology for modelling parking and traffic in the context of multiusers which can represent diverse characteristics as parking time or type of vehicles. This model will be modified to take into account AV and the necessary assumptions and discussion will be provided.</p>

Isotopic assays, including stable carbon, stable oxygen, and radiogenic strontium were measured for 37 individuals from the Talgua cave ossuaries to understand human movement and mortuary practice during Formative Period Honduras. Likelihood assignment models demonstrated that the individuals had diverse childhood geographic origins within the surrounding valleys. This shows that different kin or ethnic groups from diverse geographic origins were utilizing the ossuaries. Five possible ‘non-local’ individuals were identified from the radiogenic strontium and stable oxygen isotope datasets, suggesting minimal human movement into northeast Honduras from outside Lower Central America. The low number of ‘non-local’ individuals at Talgua Caves also suggests that trade items were acquired by down-the-line exchange processes rather than through a long-distance trade connection. This type of trade network and bioarchaeological evidence of limited ‘non-local’ individuals at Talgua Caves suggests the surrounding region was culturally distinct from Mesoamerica during the Formative Period.

In semiconductor manufacturing, wafers are grouped into lots and sent to a separate facility for assembly and test (AT) before being shipped to the customer. Up to a dozen operations are required during AT. The facility in which these operations are performed is a reentrant flow shop consisting of several dozen to several hundred machines and up to a thousand specialized tools. Each lot follows a specific route through the facility, perhaps returning to the same machine multiple times. Each step in the route is referred to as a "pass." Lots in work in process (WIP) that have more than a single step remaining in their route are referred to as multi-pass lots. The multi-pass scheduling problem is to determine machine setups, lot assignments and lot sequences to achieve optimal output, as measured by four objectives related to key device shortages, throughput, machine utilization, and makespan, prioritized in this order. The two primary goals of this research are to develop a new formulation for the multipass problem and to design a variety of solution algorithms that can be used for both planning and real-time control. To begin, the basic AT model considering only single-pass scheduling and the previously developed greedy randomized adaptive search procedure (GRASP) along with its extensions are introduced. Then two alternative schemes are proposed to solve the multipass scheduling problem. In the final phase of this research, an efficient procedure is presented for prioritizing machine changeovers in an AT facility on a periodic basis that provides real-time support. In daily planning, target machine-tooling combinations are derived based on work in process, due dates, and backlogs. As machines finish their current lots, they need to be reconfigured to match their targets. The proposed algorithm is designed to run in real time. / text

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In dieser Arbeit wird ein simultanes Quell-, Ziel-, Verkehrsmittel- und Routenwahlmodell (Modell EVA-U) entwickelt, welches ein stochastisches Nutzergleichgewicht erreicht. Die Routenwahlmodelle der Verkehrsarten sind nicht mehr Teil der Umlegungsalgorithmen, sondern in das Nachfragemodell integriert. Dadurch ist eine konsistente Bewertung aller Alternativen (der Verkehrsarten) möglich. Das Simultanmodell EVA-U stellt eine Weiterentwicklung des Simultanmodells EVA von LOHSE dar. Das EVA-U-Modell ist den universalen Logit-Modellen zuzuordnen. Die Randsummenbedingungen der Verkehrsverteilung werden beachtet. Die Bewertung der Alternativen erfolgt mittels Generalisierter Kosten. Die Abhängigkeit von Routen wird berücksichtigt, ebenso die Tagesganglinie der Verkehrsnachfrage und die Fahrpläne des ÖV-Systems. Das Modell EVA-U erlaubt auch die Berücksichtigung von Routen intermodaler Verkehrsarten (z.B. P+R). Darüber hinaus ist die Integration eines Modells des ruhenden Verkehrs möglich. / In this thesis a simultaneous Trip Generation-, Distribution-, Modal-Split and Route Choice Model (modell EVA-U) is elaborated. The model tends to reach a stochastic user equilibrium. The route choice algorithms are not longer part of an assignment procedure but part of the demand model. A consistent assessment of properties of all transport systems is possible. The simultaneous model EVA-U is an advancement of the EVA-Model by Lohse. The model EVA-U is to be assigned to the generalised logit-models. All matrix constrains are taken into account. The assessment is effected by generalised costs. The dependence of routes is taken into account. Moreover, the integration of day time and the schedules of private transport lines is possible. Furthermore, it is possible to integrate a model of parked cars and circuits of inter-modal traffic forms (park and ride) in the Model EVA-U.