Transportation planning initiatives at different administrative levels require traffic data at appropriate resolutions. This research presents a methodology for determination of optimal traffic resolution depending on the planning level under consideration. The framework is supported by a proof of concept in the form of a Geographical Zone Partitioning Software (GEZOPS) - a decision-support tool serving to fill an existing gap in the domain of high level traffic analysis tools for transportation planning. The strategy is based on multi-objective optimization using weighted agglomerative ranking & selection and evolutionary algorithms. Facility for handling geospatial constraints for contiguity and primary arterial boundaries is provided with full-scale integration with mapping and software for statistical analysis.

In contributing to the area of evolutionary algorithms, the research demonstrates the application of Restricted Growth Functions (RGF) to encode the set partition. This encoding is used with modern evolutionary algorithms such as the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Problem-specific issues such as geospatial constraints and representation provide the necessary motivation for design and development of diversity preservation strategies, crossover and mutation approaches to provide the necessary balance between exploration and exploitation. Specific algorithmic aspects and parameterization specifications are implemented to provide a platform for sensitivity analysis and comparative studies.

The Huntsville Metropolitan Planning Organization (HMPO) is used as a case study for testing the algorithms developed in this research initiative. Results from subject-matter expert assessment and validation are provided to demonstrate that the strategy produces partitions that are not only quantitatively fit but also useful from a transportation planning perspective. Scope for further research in the zone partitioning problem using other formulations is identified.