Identifying optimal earthquake evacuation routes using genetic algorithm

  • Bea Barolo Artuz Department of Physical Sciences and Mathematics, University of the Philippines Manila
  • Kathleen Mae Juadiong Department of Physical Sciences and Mathematics, University of the Philippines Manila
  • Astrid Korina Gabo Department of Physical Sciences and Mathematics, University of the Philippines Manila
  • Rhenish Simon Department of Physical Sciences and Mathematics, University of the Philippines Manila

Abstract

The disaster response team of Metropolitan Manila prepares for the 'Big One,' focusing on information dissemination as to what must be done when the earthquake happens. In order to make a quick and safe evacuation, it is necessary to formulate a clear-cut evacuation plan, specifically, to create evacuation routes. In this study, earthquake evacuation was simulated from Philippine General Hospital (PGH) to Rizal Park to identify optimal evacuation routes quantitatively using genetic algorithm (GA) and geospatial data. The problem was treated as a multi-objective optimization problem wherein the evacuation distance was minimized and the arrival probability maximized. Road networks were mapped using Geographical Information System (GIS) and information on road lengths and road blockage probability were imported to python. GA was used to search for optimal evacuation routes. The algorithm yielded a front of Pareto-optimal solutions. Subsequently, analytic hierarchical process (AHP) was applied to select the best optimal evacuation route according to preference. The best route identified has a distance of 1089.32 m and an arrival probability of 0.504. The model contributes to the preparation and planning of evacuation in the event of the 'Big One' ensuring the safest and most efficient evacuation route.

Published
2018-05-24
How to Cite
[1]
B. Artuz, K. M. Juadiong, A. K. Gabo, and R. Simon. Identifying optimal earthquake evacuation routes using genetic algorithm, Proceedings of the Samahang Pisika ng Pilipinas 36, SPP-2018-PB-15 (2018). URL: https://paperview.spp-online.org/proceedings/article/view/SPP-2018-PB-15.
Section
Poster Session B (Complex Systems, Simulations, and Theoretical Physics)