Volume XLII-3/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 93-100, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-93-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 93-100, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-93-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  06 Mar 2018

06 Mar 2018

An optimized multi agent-based modeling of smart rescue operation

S. Azimi1, M. R. Delavar2, and A. Rajabifard3 S. Azimi et al.
  • 1GIS Dept., School of Surveying and Geospatial Engineering., College of Engineering, University of Tehran, Tehran, Iran
  • 2Center of Excellence in Geomatic Engineering in Disaster Management, School of Surveying and Geospatial Engineering., College of Engineering, University of Tehran, Tehran, Iran
  • 3Department of Infrastructure Engineering, Centre for Spatial Data Infrastructures and Land Administration, the University of Melbourne, Melbourne, VIC, Australia

Keywords: Multi-agent based modeling, Resource allocation, Multiplicatively Weighted Network Voronoi Diagram, Particle Swarm Optimization, Smart rescue operation, Smart city

Abstract. After the incidence of a disaster, a high demand for first-aid and a huge number of injured will emerge at the affected areas. In this paper, the optimum allocation of the medical assistance to the injured according to a multi-criteria decision making is performed by Multiplicatively Weighted Network Voronoi Diagram (MWNVD). For consideration of the allocation of the injured in the affected area to the appropriate hospitals using the MWNVD and decreasing the gap between the estimated and expected population in the MWNVDs, Particle Swarm Optimization (PSO) is applied to the MWNVDs.
This paper proposes a multi agent-based modeling for incorporating the allocation of the medical supplies to the injured according to the generated Voronoi Diagrams of the PSO-MWNVD, wayfinding of emergency vehicles based on the minimum travel distance and time as well as using smart city facilities to expedite the rescue operation. In the proposed model, considering the priority of the injured for receiving the medical assistance, information transfer about the condition of the injured to the hospitals prior to ambulance arrival for providing appropriate treatment, updating of emergency vehicles route based on the blocked streets and etc. are optimized.
The partial difference between the estimated and expected population for receiving the medical assistance in MWNVDs is computed as 37 %, while the PSO-MWNVD decreased the mentioned difference to 6 %. The relief operation time in the proposed model compared to another multi-agent rescue operation model, which uses MWNVD and does not have some facilities of the proposed model, is improved.