A MODELING FRAMEWORK OF HIERARCHICAL EARTHQUAKE RELIEF CENTER LOCATIONS UNDER DEMAND UNCERTAINTY

Abstract

This paper presents a modeling framework for locating earthquake disaster relief centers,
developed through multidimensional and integrated perspectives of transportation engineering and
humanitarian logistics planning. The proposed framework consists of three sequential steps: 1) Seismic risk
analysis, to evaluate the vulnerability of both road network and area-covering disruptions, using the spaghetti
and meatballs method, which is a geographic information system (GIS) based analytical approach enriched
with historical earthquake statistics and earthquake fault data; 2) Travel demand analysis, to forecast travel
demand, travel behavior, travel pattern, and traffic volume, using the four-step transportation model
developed based on field traffic survey data and seismic risk analysis data; and 3) Facility location problem
analysis, to locate optimal earthquake disaster relief centers, using the hierarchical location problem model
formulated based on a meta-heuristic genetic algorithm (GA) optimization technique. To evaluate model
mechanism and performance, a preliminary model was then applied to the simulated geographical area with
simulated road network of Chiang Rai Province, Thailand. As a result, two-level hierarchical disaster relief
centers in response to earthquakes, taking into account accessibility and functional ability of transportation
networks, risk covered/uncovered demand and supply distribution, can be viably determined. In the upperlevel, a central disaster relief center is functioned to collect rescue equipment and survival bags from both
inside and outside the area and to distribute those to local disaster relief centers in the area. In the lowerlevel, three local disaster relief centers were optimally located, functioned to receive supplies from the central
disaster relief center and then distribute to demand points affected by earthquakes. The resulting model can
provide government and related agencies profound information in planning and developing either pre-disaster
or post-disaster operations.