Selecting and scheduling of improvements in urban transportation networks using metaheuristics

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dc.contributor.advisorSchonfeld, Paul Men_US
dc.contributor.authorJovanovic, Urosen_US
dc.contributor.departmentCivil Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2018-07-17T05:35:59Z
dc.date.available2018-07-17T05:35:59Z
dc.date.issued2017en_US
dc.description.abstractDeciding which projects, alternatives and/or investments should be implemented is a complex and important topic not only in transportation engineering, but in management, operations research, and economics. If the project’s benefits or costs depend on which other project is realized, then the projects are interrelated. The evaluation method computes the costs of network flows determined with the Frank-Wolfe algorithm, which is modified to consider intersection flows and delays. Intersections are modelled with pseudo-links. The methods used for choosing the optimal schedule of project improvements are: Ant Colony Optimization, Simulated Annealing and Tabu Search. The heuristic that yields the best most quickly solution is Ant Colony Optimization and it is chosen for the sensitivity analysis. The results of the sensitivity analysis show how the changes in ACO parameters and the model parameters influence the behavior of the model and the algorithm.en_US
dc.identifierhttps://doi.org/10.13016/M2TT4FW98
dc.identifier.urihttp://hdl.handle.net/1903/20766
dc.language.isoenen_US
dc.subject.pqcontrolledTransportationen_US
dc.titleSelecting and scheduling of improvements in urban transportation networks using metaheuristicsen_US
dc.typeThesisen_US

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