Land Use and Transportation Planning for Twin Cities Using a Genetic Algorithm

A new approach to future land use and transportation planning for high-growth cities is presented. The approach employs a genetic algorithm to efficiently search through hundreds of thousands of possible future plans. A new fitness function is developed to guide the genetic algorithm toward a Pareto...

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Bibliographic Details
Published in:Transportation research record 2000, Vol.1722 (1), p.67-74
Main Authors: Balling, Richard J., Taber, John, Day, Kirsten, Wilson, Scott
Format: Article
Language:English
Subjects:
Applied sciences
Buildings. Public works
Exact sciences and technology
Ground, air and sea transportation, marine construction
Transportation planning, management and economics
Urban development
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Summary:A new approach to future land use and transportation planning for high-growth cities is presented. The approach employs a genetic algorithm to efficiently search through hundreds of thousands of possible future plans. A new fitness function is developed to guide the genetic algorithm toward a Pareto set of plans for the multiple competing objectives that are involved. This set may be placed before decision makers. A Pareto set scanner also is described that assists decision makers in shopping through the Pareto set to select a plan. Some of the differences between simultaneous planning and separate planning of highly coupled twin cities also are examined.
ISSN:0361-1981
2169-4052
DOI:10.3141/1722-08