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Land use and transportation planning for twin cities using a genetic algorithm Balling, Richard J et al

By: Balling, Richard JPublication details: Transportation Research Record, 2000Description: nr 1722, s. 67-74Subject(s): USA | Land use | Transport | Planning | Urban area | Mathematical model | Decision process | 10Bibl.nr: VTI P8167:1722Location: Abstract: 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.
Item type: Reports, conferences, monographs
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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.

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