A Framework for Shelter Location Decisions by Ant Colony Optimization

Hossein Baharmand, Tina Comes


Earthquakes frequently destroy the homes and livelihoods of thousands. One of the most important concerns after an earthquake is to find a safe shelter for the affected people. Because of large numbers of potential locations, the multitude of constraints (e.g. access to infrastructures; security); and the uncertainty prevailing (e.g., number of places required) the identification of optimal shelter locations is a complex problem. Nevertheless, rapidly locating shelters and transferring the affected people to the nearest shelters are high priority in crisis situations. In this paper, we develop a framework based on Ant Colony Optimization (ACO) to support decisions-makers in the response phase. Using the same framework, we also derive recommendations for urban planning in the preparedness phase. We demonstrate our method with a case focusing on the city of Kerman, in Iran.

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