Local parks are public resources that promote human and environmental
welfare. Unfortunately, park inequities are commonplace as historically
marginalized groups may have insufficient access. Platforms exist to identify
the geographical areas that would benefit from future park improvements.
However, these platforms do not include budget, infrastructure, and
environmental considerations that are relevant to park location decisions. To
support recreational and government agencies in addressing inequities in the
distribution and quality of parks, we propose a mixed-integer program that
minimizes insufficient access, defined as weighted deviations across multiple
categories. We consider an equity-focused min-max objective and an overall
objective to minimize total weighted deviations. We apply the model to a case
study of Asheville, North Carolina. We conduct extensive data collection to
parameterize the model. In policy analyses, we consider the effects of
available budget, planning horizons, strategic demographic priorities, and
thresholds of access. The model reflects user-defined criteria and goals, and
the results suggest that the framework may be generalizable to other cities.
This study serves as the first step in the development and incorporation of
mathematical modeling to achieve social goals within the recreational setting