## 1 Introduction  
Search and rescue of victims in large-scale disasters is of great importance in disaster relief. The research of disaster relief has focused mostly on emergency supplies reserves, location problems, emergency transportation, resource allocation and evacuation [1; 2; 3; 4; 5; 6; 7], which has provided an important theoretical foundation for disaster relief and improved rescue efficiency for sure. However, the research about search and rescue in the post-disaster phase are rarely seen. The cooperation between rescue teams is essentially about task allocation. Many approaches for the task allocation problem have been proposed, such as contract net protocol [8; 9], intelligent algorithm-based approaches [10; 11; 12; 13] and auction-based approaches [14; 15; 16], etc. Contract net protocol is a market-based approach that was proposed as early as 1980 [17]. [PERSON] and [PERSON] [8] have proposed an improved contract net protocol for task allocation in agent-oriented unmanned underwater vehicle (UUV) swarm system. [PERSON] et al. [9] employed contract net protocol for task allocation at an assembly point when adjusting group members periodically. Intelligent algorithms are also frequently adopted in this problem. [PERSON] and [PERSON] [10] have applied the extended labor division model of ant colony to task allocation in a dynamic environment. [PERSON] and [PERSON] [11] have developed a novel memetic algorithm for multi-robot task allocation of inspection problems. One of the most used approaches is auction-based strategy. [PERSON] et al. [14] have used Sequential Single Item Auctions to assign tasks to agents. [PERSON] et al. [15] have developed two auction-based approaches, a centralized combinatorial auction mechanism and a distributed method. [PERSON] et al. (2016) have proposed a decentralized indicator-based combinatorial auction strategy for group task allocation. Moreover, some task allocation problems have been solved through coalition formation. The sequential and holistic coalition methods proposed in ([PERSON] et al., 2016) provided both online and offline solutions for task allocation into a group of heterogeneous mobile robots. [PERSON] et al. (2019) have provided a DCOP formulation of the coalition problem and solve it with the Max-Sum algorithm. In this paper, agent-based simulation is used to model the disaster relief. Compared with other approaches such as discrete event simulation ([PERSON] et al., 2016; [PERSON] et al., 2016), agent-based approach could describe the interaction between agents in complex systems. The agent-based approach is more appropriate to model complex systems and cope with the complexities and dynamics in complex systems ([PERSON] et al., 2016). In agent-based simulation, the conceptual model was built from the view of agents. Furthermore, the agents are autonomous ([PERSON] et al., 2016), which means they can carry out some set of operations with some degree of independence or autonomy. The agents can react to the environment and act on it, while, in discrete event simulation (DES), the model was built from the view of event. The entities in the DES are not autonomous, and they cannot make decisions on their own. Thus, the entities' status cannot be decided by themselves. There exist few researches which integrate search with cooperative rescue in disaster relief. However, search and rescue are inseparable in disaster relief. In this paper, we first construct a post-disaster environment based on multi-agent modeling. The survival probabilities of victims trapped in rubble are assumed to deteriorate with time ([PERSON] et al., 2016). Related to the search for victims, it has been proved that for randomly located targets, whether the targets can be revisited many times or not, and whether the targets are fixed or moving, Levy walks is an efficient strategy ([PERSON] et al., 2017; [PERSON] et al., 2017). In addition, [PERSON] et al. (2017) have found that the patterns of human walks and Levy walks are similar in some statistical properties.