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Computational Science, Engineering & Technology Series
ISSN 1759-3158
CSETS: 37
NEW TRENDS IN SEISMIC DESIGN OF STRUCTURES
Edited by: N.D. Lagaros, Y. Tsompanakis and M. Papadrakakis
Chapter 13

Optimal Restoration Scheduling for Earthquake Disaster

K. Nakatsu1, H. Furuta1 and Y. Nomura2

1Department of Informatics, Kansai University, Japan
2Organization of Advanced Science and Technology, Kobe University, Japan

Full Bibliographic Reference for this chapter
K. Nakatsu, H. Furuta, Y. Nomura, "Optimal Restoration Scheduling for Earthquake Disaster", in N.D. Lagaros, Y. Tsompanakis and M. Papadrakakis, (Editors), "New Trends in Seismic Design of Structures", Saxe-Coburg Publications, Stirlingshire, UK, Chapter 13, pp 399-428, 2015. doi:10.4203/csets.37.13
Keywords: delay in schedule, economic constraints, genetic algorithm, restoration scheduling, uncertainty.

Abstract
Japan has frequent natural disasters, including earthquakes and typhoons. Therefore, it is necessary to develop a comprehensive disaster prevention program based on the recognition that the damage of road networks due to very strong earthquakes may be inevitable. The main purpose of this chapter is to make a plan for an appropriate restoration of road networks after the earthquake. This study focuses on two issues to formulate the plan for the early restoration. The first problem is an allocation of groups (workers) to the disaster area. The second is a scheduling problem of an order of the repairs to the road network. In order to solve the two problems simultaneously, a genetic algorithm (GA) is applied, because it has proved to be very powerful in solving combinatorial problems. However, road networks after earthquake disasters constitute an uncertainty, that is, the restoration work does not always progress on schedule. The damage situations at disaster areas may be alterable due to aftershocks, fire disaster and bad weather. Therefore, it is important to formulate a restoration schedule that provides high robustness against changes in damage situations. To overcome those problems, an attempt is made to develop a decision support system of the optimal restoration scheduling by using some improved GAs.

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