Application of regional earthquake mitigation optimization

Abstract

A linear program was developed to help seismically active communities decide: (1) how much to spend on pre-earthquake mitigation that aims to reduce future losses versus waiting until after an event and paying for reconstruction, and (2) which of the many possible mitigation activities to fund so as to minimize overall risk. The mitigation alternatives considered are structural upgrading policies for groups of buildings. Benefits of mitigation are losses avoided in future earthquakes, including structural, non-structural, contents, and time-related losses, and casualties. The model is intended to be used as a tool to support the public regional mitigation planning process. In realistic applications, the model includes millions of variables, thus requiring a special solution method. This paper focuses on two efficient solution algorithms to solve the model—a Dantzig–Wolfe decomposition algorithm and a greedy heuristic algorithm. A comprehensive numerical study compares the two algorithms in terms of solution quality and solution time. The study shows that, compared to the Dantzig–Wolfe algorithm, the heuristic algorithm is much faster as expected, and provides comparable solution quality.