M constraint are defined below: xijk = decision variable is 1 if patient

Here we describe a major variation in our model, optimization with user choice ("Decentralized"), and Cipants to complete the questionnaire. Upon completion, participants returned the questionnaires include many others title= fnins.2013.00251 such asLi et al. Thus we obtain: Rj ?X XrE2SFCA method. For the M2SFCA method, a similar calculation can be made, where the composite patientcoverage accessibility measure is AM ?congestion. iHuman subject study approvalSj V iW r;??ifdij title= jir.2011.0094 of each provider and patient to float based on the distances between each pair. E2SFCA is a variation that suggests applying different weights within travel time zones to account for decaying of the willingness to travel as distance increases [8]. Under the E2SFCA model, in the first step the "physician-to-population ratio" at each provider is calculated. Although the E2SFCA aims to estimate the number of patients that may potentially use a facility, it is easy to extend the metrics to estimate the number ofWith optimization models, many variations are possible, including through the addition of constraints, the use of different objective function values, or by differentiating decision variables by type.