n396065SE Academic Article uri icon

abstract

  • Copyright 2017 Inderscience Enterprises Ltd. The purpose of this study is to present a taxonomy of expected distance functions (EDFs). An EDF is the expected (where expected is used in the strict probabilistic sense) distance formula for a given metric between two algebraically defined regions (e.g., the expected Euclidean distance between a semi-circle of radius r centred at (x1, y1) that has a known bivariate probability density function in r and and a line segment beginning at (x2, y2) and ending at (x3, y3) that has a known probability density function along its length). A modest library of EDFs for various metrics (rectilinear, Euclidean, Tchebychev, etc.) between pairs of common geometric shapes (e.g., lines, semi-circles, rectangles, etc.) is presented. The taxonomy of EDFs contained herein is by no means meant to be an exhaustive list. Indeed, it is limited in scope to those considered to be of practical importance to geographic information, transportation science, and mathematical modelling professionals.

published proceedings

  • International Journal of Mathematics in Operational Research

author list (cited authors)

  • Hale, T. S., Lutz, H. S., & Huq, F.

publication date

  • January 1, 2017 11:11 AM