Developing a Multi-agent Based Modeling for Smart Search and Rescue Operation

One important issue aftermath of disasters is the optimum allocation of the medical assistance to the demanded locations. 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). Particle Swarm Optimization (PSO) is applied to optimize the MWNVDs. In this paper, two types of multi-agent rescue models for incorporating the allocation of the medical supplies to the injured locations according to the generated PSO-MWNVDs, wayfinding of emergency vehicles as well as using smart city facilities were proposed. In one of the proposed model, 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 and updating of ambulance route were considered. Another proposed model has facilities of coordination of emergency vehicles with traffic lights in the intersection and updating of fire engine route compared to the facilities of the first one. 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%. Also, the time evaluation of the mentioned proposed models and another multi-agent rescue operation model, which uses MWNVD and does not have the studied smart facilities was performed. The results show that the response time of ambulances to the injured and the ambulance mission duration in the proposed model, that has more smart facilities, is improved to other models.