The transparency of the online user interface facilitated stakeholder buy-in.
The model employs time-tested System Dynamics methods, including numerous stocks and feedback loops, delays, and behavioral expectation trending algorithms (Image adapted from online model).
The model employs nonlinear optimization using a genetic algorithm to help Council staff find optimal build strategies.
The model accepts key parameters input as probability distributions, rather than point estimates. The model runs using Monte Carlo simulation, permitting incorporation of portfolio risk metrics (e.g., CVaR) into the optimization objective function.