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dc.contributor.advisorReinschmidt, Kenneth F
dc.contributor.advisorKang, Julian H
dc.creatorFaghihi, Vahid
dc.date.accessioned2015-01-09T20:25:40Z
dc.date.available2016-05-01T05:31:04Z
dc.date.created2014-05
dc.date.issued2014-04-04
dc.date.submittedMay 2014
dc.identifier.urihttp://hdl.handle.net/1969.1/152576
dc.description.abstractConstruction project scheduling is one of the most important tools for project managers in the Architecture, Engineering, and Construction (AEC) industry. The Construction schedules allow project managers to track and manage the time, cost, and quality (i.e. Project Management Triangle) of projects. Developing project schedules is almost always troublesome, since it is heavily dependent on project planners’ knowledge of work packages, on-the-job-experience, planning capability, and oversight. Having a thorough understanding of the project geometries and their internal interacting stability relations plays a significant role in generating practical construction sequencing. On the other hand, the new concept of embedding all the project information into a three-dimensional (3D) representation of a project (a.k.a. Building Information Model or BIM) has recently drawn the attention of the construction industry. In this dissertation, the author demonstrates how to develop and extend the usage of the Genetic Algorithm (GA) not only to generate construction schedules, but to optimize the outcome for different objectives (i.e. cost, time, and job-site movements). The basis for the GA calculations is the embedded data available in BIM of the project that should be provided as an input to the algorithm. By reading through the geometry information in the 3D model and receiving more specific information about the project and its resources from the user, the algorithm generates different construction schedules. The output Pareto Frontier graphs, 4D animations, and schedule wellness scores will help the user to find the most suitable construction schedule for the given project.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectConstruction Project Schedule
dc.subjectBuilding Information Model
dc.subjectGenetic Algorithm
dc.subjectOptimization
dc.titleAutomated and Optimized Project Scheduling Using BIM
dc.typeThesis
thesis.degree.departmentCivil Engineering
thesis.degree.disciplineCivil Engineering
thesis.degree.grantorTexas A & M University
thesis.degree.nameDoctor of Philosophy
thesis.degree.levelDoctoral
dc.contributor.committeeMemberAnderson, Stuart D
dc.contributor.committeeMemberWalewski, John
dc.type.materialtext
dc.date.updated2015-01-09T20:25:40Z
local.embargo.terms2016-05-01
local.etdauthor.orcid0000-0002-6264-1378


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