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Open AccessJournal ArticleDOI

Developing an Agent-Based Simulation System for Post-Earthquake Operations in Uncertainty Conditions: A Proposed Method for Collaboration among Agents

Navid Hooshangi, +1 more
- 15 Jan 2018 - 
- Vol. 7, Iss: 1, pp 27
TLDR
The overall results showed that considering uncertainty in task allocation can be a highly advantageous in the disaster environment and such systems can be used to manage and prepare for natural hazards.
Abstract
Agent-based modeling is a promising approach for developing simulation tools for natural hazards in different areas, such as during urban search and rescue (USAR) operations. The present study aimed to develop a dynamic agent-based simulation model in post-earthquake USAR operations using geospatial information system and multi agent systems (GIS and MASs, respectively). We also propose an approach for dynamic task allocation and establishing collaboration among agents based on contract net protocol (CNP) and interval-based Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods, which consider uncertainty in natural hazards information during agents’ decision-making. The decision-making weights were calculated by analytic hierarchy process (AHP). In order to implement the system, earthquake environment was simulated and the damage of the buildings and a number of injuries were calculated in Tehran’s District 3: 23%, 37%, 24% and 16% of buildings were in slight, moderate, extensive and completely vulnerable classes, respectively. The number of injured persons was calculated to be 17,238. Numerical results in 27 scenarios showed that the proposed method is more accurate than the CNP method in the terms of USAR operational time (at least 13% decrease) and the number of human fatalities (at least 9% decrease). In interval uncertainty analysis of our proposed simulated system, the lower and upper bounds of uncertain responses are evaluated. The overall results showed that considering uncertainty in task allocation can be a highly advantageous in the disaster environment. Such systems can be used to manage and prepare for natural hazards.

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Citations
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Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran

TL;DR: The hybrid FAHP-ANN model accurately identified the highest earthquake vulnerability in densely populated areas with dilapidated building infrastructure and is useful for decision makers with a scientific basis to develop earthquake risk management strategies.
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Spatio-temporal simulation of the novel coronavirus (COVID-19) outbreak using the agent-based modeling approach (case study: Urmia, Iran)

TL;DR: The results of the ABM indicated that school and educational center closures in Urmia city, reduced the number of infected people by 4.96% each week on average and 49.61% in total from February 21 until May 10, respectively.
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Agent-based evaluation of humanitarian relief goods supply capability

TL;DR: In this article, the authors developed a prototype of a spatially explicit agent-based model and used it to evaluate the deviation of end products between supply and demand for humanitarian relief goods in the areas affected by disaster within a specified time frame.
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Agent-based modeling and simulation to assess flood preparedness and recovery of Manufacturing Small and Medium-sized Enterprises

TL;DR: Results indicate the effectiveness of combinations of these adaptation measures in relation to a one in 1000 year flood event that has been modeled and simulated in a key industrial area of the UK which, in addition to having experienced severe flooding, has a high concentration of SMEs.
Proceedings ArticleDOI

A survey of task allocation techniques in MAS

TL;DR: In this paper, the main techniques used for task allocation algorithms, categorising them based on the techniques used, focusing mainly on recent works, are presented and compared, trying to find gaps in the literature and to propose the most promising ones.
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