Examining the LEED Rating System Using Approximate Inverse Optimization

Abstract

The Leadership in Energy and Environmental Design (LEED) rating system is the most recognized green building certification program in North America. In order to be LEED certified, a building must earn a certain number of points, which are obtained through achieving certain credits or design elements. Prior to LEED version 3, each credit was worth one point. In this study, we develop an inverse optimization approach to examine how building designers intrinsically valued design elements in LEED version 2. Due to the large dimensionality of the inverse optimization problem, we develop an approximation to improve tractability. We apply our method to 18 different LEED-certified buildings in the United States. We find that building designers did not value all credits equally and that other factors such as cost and certification level play a role in how the credits are valued. Overall, inverse optimization may provide a new method to assess historical data and support the design of future versions of LEED.