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Ant Colony Optimization Model for Tsunamis Evacuation Routes
Author(s) -
Forcael Eric,
González Vicente,
Orozco Francisco,
Vargas Sergio,
Pantoja Alejandro,
Moscoso Pablo
Publication year - 2014
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/mice.12113
Subject(s) - ant colony optimization algorithms , drill , shortest path problem , nest (protein structural motif) , emergency evacuation , ant colony , population , computer science , operations research , natural disaster , simulation , geography , engineering , artificial intelligence , graph , biology , mechanical engineering , biochemistry , demography , theoretical computer science , sociology , meteorology
Natural disasters such as earthquakes and tsunamis foster the creation of effective evacuation strategies to prevent the loss of human lives. This article proposes a simulation model to find out optimum evacuation routes, during a tsunami using Ant Colony Optimization (ACO) algorithms. ACO is a discrete optimization algorithm inspired by the ability of ants to establish the shortest path from their nest to a food source, and vice versa, using pheromones. The validation of the model was carried out through two drills, which were conducted in the coastal town of Penco, Chile. This town was strongly affected by an 8.8 Mw earthquake and tsunami over February 2010. The first drill was held with minimum information, leaving the population to act randomly and intuitively. The second drill was carried out with information provided by the model, inducing people to use the optimized routes generated by the ACO algorithm. The results showed that, in case of an emergency, conventional evacuation routes showed longer escape times compared to those produced by the model developed in this research.

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