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Computational Science, Engineering & Technology Series
ISSN 1759-3158
Edited by: J. Kruis, Y. Tsompanakis and B.H.V. Topping
Chapter 12

Application of Genetic Algorithms to Disaster Restoration under Uncertain Environments

H. Furuta1, K. Nakatsu2 and K. Ishibashi3

1Faculty of Informatics, Kansai University, Osaka, Japan
2Department of Modern Life, Osaka Jonan Women's Junior College, Osaka, Japan
3Data Science Research Center at the Research Institute for Socionetwork Strategies, Kansai University, Osaka, Japan

Full Bibliographic Reference for this chapter
H. Furuta, K. Nakatsu, K. Ishibashi, "Application of Genetic Algorithms to Disaster Restoration under Uncertain Environments", in J. Kruis, Y. Tsompanakis and B.H.V. Topping, (Editors), "Computational Techniques for Civil and Structural Engineering", Saxe-Coburg Publications, Stirlingshire, UK, Chapter 12, pp 281-304, 2015. doi:10.4203/csets.38.12
Keywords: disasters, infrastructure, restoration schedule, genetic algorithm, uncertainty, delay of schedule.

In recent years, serious disasters such as typhoons, earthquakes, tsunamis, heavy rains, landslides, etc. have frequently occurred all over the world. It is expected that large earthquakes may occur in Japan in the near future so under such conditions, it is necessary to reduce the damage due to the disaster and shorten the restoration works as much as possible. Our life is realized based upon the daily use of various infrastructures, especially road networks. Those roads form the complicated networks whose functions are mutually interrelated. After major disasters, road networks play important roles in rescue, evacuation activities, extinguishing fires, and disaster-relief activities. Damage to a road network is associated with severe impact on the daily life and economic activities of people. So far the genetic algorithm (GA) has been applied in disaster restoring problems. However, in order to establish a practical restoration and recovery scheduling, it is inevitable that the various uncertainties involved in the process of restoration processes be considered. Namely, road networks after disasters have uncertain environments, i.e., the actual restoration process should be performed by considering various uncertainties simultaneously. Consequently, a GA has been applied to search solutions for the uncertain problems by combining probabilistic approaches. In this paper, several studies relating to optimal restoration with uncertain environments will be reviewed and some problems to be overcome will be elucidated. Furthermore, an attempt is made to develop new methods which can treat various uncertainties without using probability theory directly. They can provide engineers with robust restoration schedules. Using the methods, it is possible to obtain practical and efficient solutions without complicated computations. Several numerical examples are presented to demonstrate the applicability of the methods to practical disaster restoration scheduling problems.

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