Multi Agent With Multi Behavior Based on Particle Swarm Optimization (PSO) for Crowd Movement in Fire Evacuation

A Simulation of human behavior are challenge topics of research in computer intelligent that has many benefits, such as to create a simulation of evacuation plan in a building when a disaster happens, like a fire and an earthquake. For evacuation of the building simulation of human behavior is needed to know which path will be passed through by the crowd. This animation simulation will use particle swarm algorithm optimization as the algorithm based with multiple behaviors and multiple targets. In this simulation, we add the behaviour of avoiding crashed between human and the algorithm modification is done which is a leader character is added. The leader behavior will lead the other agent to get out of the room. This agent based simulation movement will simulate movement in a room when an alarm signal is given, then the agent will get out of the room either individually or in groups. In this research we will use three scenario. We will compared the use of multiple target than single target and the use of leader follower behavior in any different number of agents. From the test result is obtained that the use of multiple target is much better result than use a single target and the behavior of the agent is depend on the movement of the crowd. Utilization of multibehavior with the leader characteristic who direct the other agent to reach target is more useful because it will reach the target more faster but the number of agents will affect the optimal number of leader needed.