Theses and Dissertations from UMD

Permanent URI for this communityhttp://hdl.handle.net/1903/2

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM

More information is available at Theses and Dissertations at University of Maryland Libraries.

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2015 - 20182

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Author: search.filters.author.Shayanfar, ElhamSubject: search.filters.subject.Transportation

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    Planning and Scheduling Interrelated Road Network Projects by Integrating Cell Transmission Model and Genetic Algorithm
    (2018) Shayanfar, Elham; Schonfeld, Paul M; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    In systems with interrelated alternatives, the benefits or costs of each alternative depend on which other alternatives are selected and when they are implemented. System interrelations and uncertainties in various elements of transportation systems such as future demand, make it difficult to evaluate project impacts with analytical methods. This study proposes a general and modular framework for planning and scheduling interrelated infrastructure projects under uncertainties. The method should be general enough to address the planning problem for any interrelated system in a wide range of applications. The goal is to determine which projects should be selected and when they should be implemented to minimize the present value of total system cost, subject to a cumulative budget flow constraint. For this purpose, the scheduling problem is formulated as a non-linear integer optimization problem that minimizes the present value of system cost over a planning horizon. The first part of this dissertation employs a simple traffic assignment model to evaluate improvement alternatives. The algorithm identifies potential locations within a network that needs improvements and considers multiple improvement alternatives at each location. Accordingly, a probabilistic procedure is introduced to select the optimal improvement type for the candidate locations. The traffic assignment model is used to evaluate the objective function and implicitly compute project interrelations, with a Genetic Algorithm (GA) developed to solve the optimization problem. In the second part of the dissertation, the traffic assignment model is replaced with a more detailed evaluation model, namely a Cell Transmission Model (CTM). The use of CTM significantly improves the model by tracking queues and predicating queue build-up and dissipation, as well as backward propagation of congestion waves. Finally, since GA does not guarantee global optimum, a statistical test is employed to test the optimality of the GA solution by estimating the probability of arriving at a better solution. In effect, it is shown that the probability of finding a better solution is negligible, thus demonstrating the soundness of the GA solution.
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    PRIORITIZING AND SCHEDULING INTERRELATED ROAD PROJECTS USING METAHEURISTIC ALGORITHMS
    (2015) Shayanfar, Elham; schonfeld, paul m; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Projects are considered interrelated when their benefits or costs depend on which other projects are implemented. Selection and scheduling of interrelated projects is a challenging optimization problem which has applications in various fields including economics, operations research, business, management and transportation. The goal is to determine which projects should be selected and when they should be funded in order to minimize the total system cost over a planning horizon subject to a budget constraint. The budget is supplied by both external and internal sources from fuel tax revenues. This study then applies three meta-heuristic algorithms including a Genetic Algorithm (GA), Simulated Annealing (SA) and, Tabu Search (TS) in seeking efficient and consistent solutions to the selection and scheduling problem. These approaches are applied to a special case of link capacity expansion projects to showcase their functionality and compare their performance in terms of solution quality, computation time and consistency.