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Partitioning Vertical Evacuation Areas in Umeda Underground Mall to Minimize the Evacuation Completion Time

  • Ryo Yamamoto
  • Atsushi TakizawaEmail author
Article
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Abstract

When an underground mall is flooded, the shoppers should be evacuated to a building connected to the mall. However, the number of evacuees from a large-scale underground mall will exceed the capacity of the evacuation center. Furthermore, the evacuation time may be delayed. This paper proposes a mathematical programming problem that minimizes the evacuation completion time on a general planar graph of a partitioned evacuation area with a specified sink capacity. We also propose a workflow for translating the general geometric spatial data to graphical data. The problem is applied to the real spatial data and evacuation setting of Umeda underground mall in Osaka, Japan. The problem’s performance is compared with that of the conventional problem that minimizes the total evacuation distance, and its accuracy is confirmed in a multi-agent simulation. The validity of the proposed method is also discussed.

keywords

Evacuation planning Vertical evacuation Umeda underground mall Dynamic tree network Mixed integer programing Multi-agent simulation 

Notes

Acknowledgements

This study is partially supported by Grant-in-Aid for Scientific Research (A) and JST CREST innovative algorithm foundation for big data.

References

  1. 1.
    Osaka Prefecture (2013). About the tsunami inundation assumption (commentary). http://www.pref.osaka.lg.jp/attach/31241/00271160/95kaisetu.pdf. Accessed 1 Dec 2018.
  2. 2.
    Osaka City Underground Space Infiltration Council (2016). Underground space flood control plan of Osaka station area, ver.1 (reference, latter half). http://www.city.osaka.lg.jp/kikikanrishitsu/cmsfiles/contents/0000259/259323/osakaekitiku-shinsuitaisakukeikaku3.pdf. Accessed 1 Dec 2018.
  3. 3.
    Takizawa, A., Takagi, N., & Taniguchi, Y. (2015). Vertical evaluation simulation in Umeda underground mall in case of flooding. Annual Journal of Unban Disaster Reduction Research, 2, 35–38.Google Scholar
  4. 4.
    Mamada, S., Uno, T., Makino, K., & Fujishige, S. (2005). A tree partitioning problem arising from an evacuation problem in tree dynamic networks. Journal of the Operations Research Society of Japan, 48(3), 196–206.CrossRefGoogle Scholar
  5. 5.
    Helbing, D., Farkas, I., Molnar, P., & Vicsek, T. (2001). Simulating of pedestrian crowds in normal and evacuation situations. In M. Schreckenberg & S. D. Sharma (Eds.), Pedestrian and evacuation dynamics (pp. 21–58). Berlin: Springer.Google Scholar
  6. 6.
    Ford, L. R., & Fulkerson, D. R. (1958). Constructing maximal dynamic flows from static flows. Operations Research, 6, 419–433.CrossRefGoogle Scholar
  7. 7.
    Ford, L. R., & Fulkerson, D. R. (1962). Flows in networks. Princeton: Princeton University Press.Google Scholar
  8. 8.
    Minieka, E. (1973). Maximal, lexicographic, and dynamic network flows. Operations Research, 21, 517–527.CrossRefGoogle Scholar
  9. 9.
    Takizawa, A., Inoue, M., & Katoh, N. (2012). An emergency evacuation planning model using the universally quickest flow. The Review of Socionetwork Strategies, 6, 15–28.CrossRefGoogle Scholar
  10. 10.
    Yang, K. S., Shekhar, A. H., Oliver, D., & Shekhar, S. (2013). Capacity-constrained network-Voronoi diagram: A summary of results. In Advances in Spatial and Temporal Databases—13th International Symposium, pp. 56–73.Google Scholar
  11. 11.
    Kamiyama, N., Katoh, N., & Takizawa, A. (2006). An efficient algorithm for evacuation problem in dynamic network flows with uniform arc capacity. IEICE Transaction on Fundamentals, E89-D(8), 2372–2379.Google Scholar
  12. 12.
    Kimura, T., Sano, T., Hayashida, K., Takeichi, N., Minegishi, Y., Yoshida, Y., et al. (2009). Representation of crowd in multi-agent model—development of pedestrian simulation system Simtread. Journal of Architecture and Planning (Transactions of AIJ), 74(636), 371–377.CrossRefGoogle Scholar

Copyright information

© Springer Japan KK, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Urban Engineering, Graduate School of EngineeringOsaka City UniversityOsakaJapan
  2. 2.Department of Housing and Environmental Design, Graduate School of Human Life ScienceOsaka City UniversityOsakaJapan

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