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.