Abstract
Efficient and rapid rescue activities are vital in the immediate aftermath of a large-scale disaster. However, the locations of demanders (those requiring special care or assistance) and responders (those supporting or assisting the demanders) are often widely separated. In this paper, we propose a method of supporting efficient travel and navigation for rescue activities using fuzzy c-means clustering and a genetic algorithm. We also propose an optimization method that takes into consideration the difference in workload required by demanders, compatibility between responders and demanders, and the urgency of demanders. We then demonstrate the efficiency of our proposed method based on numerical simulations and field experiments using a web application that incorporates the method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Imada S, Nakajima J, Furukawa M (2016) Practical solution for n-TSP by use of LCO. The Japan Society for Precision Engineering Spring Meeting, H19
Kimura M, Osaragi T, Oki T (2016) Efficiency indices and traveling method for safety confirmation after a large earthquake. Papers and proceedings of the geographic information systems association (CD-ROM), C-4-4
Knuth DE (2006) The art of computer programming, 14, Fascicle 1
Nakayama T, Maeda M, Nakanishi S (2004) Transport planning of supplies using genetic algorithms under consideration for roads of plural vehicles. In: The 21st fuzzy system symposium, vol 20, pp 310–313
Ni Y (1997) A genetic algorithm for the traveling salesman problem. J Fac Int Stud Utsunomiya Univ 3:31–40
Ogawa M, Inoue M (2014) Enumerating all the optimal solutions of multiple travelling salesman problem by using Simpath Algorithm. IEICE Technical Report IBISML 2014-78, Information Processing Society of Japan, vol 114(306), pp 321–328
Okabayashi K, Nakamura A, Ando N, Yamada T, Taniguchi E (2011) Distribution model for relief supply considering the priority of refuses in the aftermath of a disaster. Proc JSCE D1, 67(5):887–897
Ono T, Kanagawa A, Takahashi H (2004) Heuristic solution for multiple traveling salesman problems with multiple depots using fuzzy C-means clustering method. IEICE, A, J87-A(7):938–948
Osaragi T, Niwa I (2018) Development of system for real-time collection, sharing, and use of disaster information. In: The 21st AGILE conference on geographic information science, geospatial technologies for all, Lecture notes in geoinformation and cartography. Springer, pp 211–229
SankeiBiz (2018) West Japan heavy rain—shortage and spatial bias of volunteers, https://www.sankeibiz.jp/econome/news/180723/ecc1807230901004-n1.html. Accessed 7 Aug 2018
Suto A, Tokunaga Y (2002) A study on relief goods distribution planning based on suffering situations and countermeasures. Proc JSCE 695(IV-54):67–75
Takamura H, Yamada R (2018) A study on construction of supporting activities to monitor the elderly in disasters in the large cities -Through the activities in Sumida Ward in the Great East Japan Earthquake, vol 5, pp 36–42. Studies on Social Welfare, Toyo University
Tanaka T (2018) Support for disaster prevention volunteers, review and recommendation database of 10 years restoration. Website of Hyogo Prefecture, 167. https://web.pref.hyogo.lg.jp/kk41/documents/000039304.pdf. Accessed 7 Aug 2018 (in Japanese)
Usui M, Hatayama M, Fukuyama K (2013) A study on safety confirmation with information system in local community. J Soc Saf Sci 16:1–10
Acknowledgements
A portion of this work is supported by Cross-ministerial Strategic Innovation Promotion Program (SIP). The authors wish to express their sincere thanks to Japan Science and Technology Agency (JST).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Osaragi, T., Kimura, M., Oki, T. (2019). Efficient Regional Travel for Rescue and Relief Activities in a Disaster. In: Geertman, S., Zhan, Q., Allan, A., Pettit, C. (eds) Computational Urban Planning and Management for Smart Cities. CUPUM 2019. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-030-19424-6_23
Download citation
DOI: https://doi.org/10.1007/978-3-030-19424-6_23
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-19423-9
Online ISBN: 978-3-030-19424-6
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)