Please use this identifier to cite or link to this item:
Title: Bi-level genetic algorithm approach for 3D road alignment optimization
Authors: FAN TAO
Keywords: 3D road alignment, bi-level algorithm, horizontal alignment, vertical alignment, genetic algorithms
Issue Date: 12-May-2005
Citation: FAN TAO (2005-05-12). Bi-level genetic algorithm approach for 3D road alignment optimization. ScholarBank@NUS Repository.
Abstract: Genetic algorithms (GA) are an optimization method based on evolutionary principles. In the first part of the research, the GA has been used as the basis to develop methods to optimize the horizontal and vertical alignments separately. In the horizontal alignment problem, the objective is to determine the best road alignment in 2D horizontal space. For each horizontal road alignment, it is necessary to determine the best vertical alignment among the many possible vertical alignments. The 3D alignment is obtained by combining the horizontal and vertical alignments. The case studies show that the proposed approach can very quickly and consistently improve the quality of the solutions for both the horizontal and vertical alignment problems using an iterative procedure.
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
master thesis.pdf1.17 MBAdobe PDF



Page view(s)

checked on Dec 30, 2018


checked on Dec 30, 2018

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.