Cluster Computing

, Volume 22, Supplement 4, pp 8859–8867 | Cite as

Implementation of emergency logistics distribution decision support system based on GIS

  • Chengming QiEmail author
  • Jianjun Fang
  • Lianying Sun


In order to reduce the damage of earthquake, a decision support system based on geographic information system (GIS) for the distribution and transportation of emergency materials after the earthquake is designed and implemented. The allocation and transportation of emergency supplies and transport routes were chosen as the study subjects. The occurrence of an earthquake disaster cannot be prevented. It often results in a large number of casualties, collapsed houses and damaged infrastructure. Therefore, timely assistance is an important measure to avoid further casualties. The results show that the system provides decision makers with a visual aid to the emergency materials distribution plan. Therefore, Matlab software programming can realize the model and its algorithm. The program is compiled into a platform callable file. The two submodule systems of emergency material allocation and transportation and the optimal path of vehicle transportation are combined. The optimization of material allocation model and the distribution system of emergency supplies after the earthquake are of theoretical and practical significance.


Earthquake Emergency supplies GIS Matlab software 



This work was supported in part by the Beijing Education Committee Science and Technology Plan General Project; by the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions under Grant CIT&TCD20150314; and by the National Key R&D Program of China under Grant 2016YFC0802107.


  1. 1.
    Rodríguez-Espíndola, O., Albores, P., Brewster, C.: GIS and optimisation: potential benefits for emergency facility location in humanitarian logistics. Geosciences 6(2), 18 (2016)CrossRefGoogle Scholar
  2. 2.
    Moreno, A., Alem, D., Ferreira, D.: Heuristic approaches for the multiperiod location-transportation problem with reuse of vehicles in emergency logistics. Comput. Oper. Res. 69, 79–96 (2016)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Sterk, M., Praprotnik, M.: Improving emergency response logistics through advanced GIS. Open Geospat. Data Softw. Stand. 2(1), 1 (2017)CrossRefGoogle Scholar
  4. 4.
    Ahmed, A.: Role of GIS, RFID and handheld computers in emergency management: an exploratory case study analysis. JISTEM J. Inf. Syst. Technol. Manag. 12(1), 3–27 (2015)Google Scholar
  5. 5.
    Gavidia, J.V., Gavidia, J.V.: A model for enterprise resource planning in emergency humanitarian logistics. J. Humanit. Logist. Supply Chain Manag. 7(3), 246–265 (2017)CrossRefGoogle Scholar
  6. 6.
    Zhang, F., Zhong, S., Yao, S., Wang, C., Huang, Q.: Ontology-based representation of meteorological disaster system and its application in emergency management: illustration with a simulation case study of comprehensive risk assessment. Kybernetes 45(5), 798–814 (2016)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Zhou, Y., Liu, J., Zhang, Y., Gan, X.: A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems. Transp. Res. Part E Logist. Transp. Rev. 99, 77–95 (2017)CrossRefGoogle Scholar
  8. 8.
    Ozguven, E.E., Horner, M.W., Kocatepe, A., Marcelin, J.M., Abdelrazig, Y., Sando, T., Moses, R.: Metadata-based needs assessment for emergency transportation operations with a focus on an aging population: a case study in Florida. Transp. Rev. 36(3), 383–412 (2016)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Urban Rail Transit and LogisticsBeijing Union UniversityBeijingChina

Personalised recommendations