Monte Carlo based Algorithm for Scoring Grid Systems

Abstract

We evaluate Monte Carlo based algorithm for scoring grid systems. The former were used to describe features of the area under study. This was done to select suitable features for City Information Modelling. These algorithms measures path of shortest distance. However, shortest distance does not always ensures shortest time. The algorithm works by pairing multiple iterations of two random numbers in a polygon. The mean of shortest path between these points is calculated. Thus grid systems with shorter paths will return a lower value as compared to grid systems with longer paths. This was applied to GIS systems in urban planning to rate the feasibility of different grid systems. It is a heuristic algorithm that tells us to about the nature of grid system. Instead of measuring the geometry of every path in a grid it eases the workflow of an urban planner by automation.