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.
Highlights
Natural hazards such as earthquakes cause large-scale casualties, injuries and the destruction of housing in residential areas [1,2]
The proposed method was evaluated by numerical simulation and a comparison with the contract net protocol (CNP) algorithm
In order to examine the effect of uncertainty, the CNP method involved in two assumptions
Summary
Natural hazards such as earthquakes cause large-scale casualties, injuries and the destruction of housing in residential areas [1,2]. Using simulators allows for the analysis of different strategies in dealing with crises and optimizes the decision-making, while minimizing losses [3]. Applying an agent-based simulation model to earthquake search and rescue operations can be a good alternative to traditional decision-making methods. Multi agent systems (MASs) making it possible to simulate building demolition, damage to urban infrastructure, injuries, search and rescue teams [4]. MASs deal with complex systems by emphasizing the interaction between agents and dividing the system into sub-sectors of the environment and other actors [5]. Task allocation plays an important role in coordinating an MAS within a set of agents [6,7]
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