Developing a Spatio-Temporal Decision Support System to Plan the Task Allocation of Relief Workers in the Post-Earthquake
Subject Areas : GISNahid Bahrami 1 , Alireza Vafaeinejad 2 , Aliasghar Alesheikh 3
1 - Faculty of Environment and Energy, Islamic Azad University, Science and Research Branch, Tehran, Iran.
2 - Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran. *(Corresponding Author)
3 - Faculty of Geodesy and Geomatics Engineering, Khajeh Nasir Toosi University of Technology, Tehran, Iran
Keywords: Decision Support System, Spatio-Temporal modeling, Task allocation, Search & Rescue. ,
Abstract :
Background and Objective: Iran is highly affected by earthquakes, due to frequent faults in its geographical scope. In this regard, the first and most important action after an earthquake is relief and rescue. Relief's appropriate, correct, and efficient management of relief workers will considerably reduce earthquake injuries, especially the loss of life. In this research, using spatio-temporal modeling of activities and relief workers, a system is being proposed for relief and rescue management after an earthquake for the optimization of task allocation to relief workers.
Material and Methodology: As part of the research purpose, a model based on auctions was developed using parameters affecting relief workers after an earthquake, namely, the expertise of relief workers, the timing of the activities, and the distance to the damaged area, because of the dynamics of the environment at the time.
Findings: In the urban environment, a spatio-temporal decision support system with an auction algorithm was implemented to plan and optimize task allocation for relief workers after the earthquake.
Discussion and Conclusion: By simulating and implementing the activities of relief and rescue teams after the earthquake in a spatial information system, the feasibility of the proposed spatio-temporal dynamic modeling for task allocation to relief workers is validated. In addition to improving the performance of relief and rescue teams, the model provided insight into the effectiveness of task allocation. The results of this study can be used to inform future disaster response strategies.
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