A methodology for the numeric time-cost forecast and pareto optimization of large Injection projects in tunneling
Citation Link: https://doi.org/10.15480/882.3840
Publikationstyp
Doctoral Thesis
Date Issued
2021
Sprache
English
Author(s)
Advisor
Title Granting Institution
Technische Universität Hamburg
Place of Title Granting Institution
Hamburg
Examination Date
2021-06-01
Institut
TORE-DOI
First published in
Number in series
49
Citation
Technische Universität Hamburg (2021)
Publisher
Technische Universität Hamburg, Institut für Geotechnik und Baubetrieb
Peer Reviewed
true
ISBN of container
978-3-936310-51-1
This thesis deals with selecting, implementing, testing, and evaluating numerical methods to support large construction projects’ construction management. The methods are bundled in a tool, which uses real-time construction process data measured on the construction site to compute project time and cost forecasts. These predictions are then combined in a numerical optimization algorithm to determine the Pareto optimal number and operating time of construction site machinery.
Subjects
tunneling
optimization
genetic algorithm
injection grouting
graph theory
statistics
construction management
simulation
neural networks
time- and cost forecast
discrete event simulation
DDC Class
690: Hausbau, Bauhandwerk
Publication version
publishedVersion