Multiobjective Urban Planning Using Genetic Algorithm

A genetic algorithm was used to search for optimal future land-use and transportation plans for a high-growth city. Millions of plans were considered. Constraints were imposed to ensure affordable housing for future residents. Objectives included the minimization of traffic congestion, the minimizat...

Full description

Saved in:
Bibliographic Details
Published in:Journal of urban planning and development 1999-06, Vol.125 (2), p.86-99
Main Authors: Balling, Richard J, Taber, John T, Brown, Michael R, Day, Kirsten
Format: Article
Language:English
Subjects:
Applied sciences
Buildings. Public works
Exact sciences and technology
TECHNICAL PAPERS
Urban development
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A genetic algorithm was used to search for optimal future land-use and transportation plans for a high-growth city. Millions of plans were considered. Constraints were imposed to ensure affordable housing for future residents. Objectives included the minimization of traffic congestion, the minimization of costs, and the minimization of change from the status quo. The genetic algorithm provides planners and decision makers with a set of optimal plans known as the Pareto set. The value of each plan in the Pareto set depends on the relative importance that decision makers place on the various objectives.
ISSN:0733-9488
1943-5444
DOI:10.1061/(ASCE)0733-9488(1999)125:2(86)