Multi-particle-swarm-cooperative-evolution-based simulated optimization method for human-vehicle mixed evacuation

Abstract

The invention provides a multi-particle-swarm-cooperative-evolution-based simulated optimization method for human-vehicle mixed evacuation. With a particle swarm optimization algorithm, a problem of human-vehicle mixed evacuation in a large building or a road network integrated environment can be solved. Evaluation processes, including a mixed evacuation process of human beings and vehicles, of evacuated individuals can be simulated by using the particle evaluation process. On the basis of a pheromone-based multi-particle-swarm communication mechanism, interaction and information sharing between people and vehicles are simulated, so that a defect that the existing particle swarm algorithm only considers interaction between particles but ignores the influence on the particle moving process by the environment can be overcome. Competition and cooperation of different traffic objects during the human-vehicle mixed evacuation process can be simulated well; an evacuation optimization scheme meeting multiple target requirements is formed; and a reasonable and efficient decision-making basis is provided.

Description

technical field [0001] The invention belongs to the field of cross application of intelligent computing and operations research, specifically a simulation optimization method for mixed evacuation of people and vehicles based on multi-particle swarm collaborative evolution, which mainly solves problems in large buildings and road network integration environments through particle swarm optimization algorithm. The human-vehicle mixed evacuation problem uses the movement process of particles to simulate evacuation individuals, including the mixed evacuation process of personnel and vehicles, and uses the pheromone-based multi-particle swarm communication mechanism to simulate the interaction and information sharing between personnel and vehicles. Background technique [0002] The problem of mixed evacuation of people and vehicles in the environment of large buildings and road network integration is to evacuate a large number of people gathered in large buildings in emergency situ...

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Problems solved by technology

[0005] Although the particle swarm optimization algorithm has the advantage of being simple and fast, there are two main shortcomings that limit its performance: on the one hand, the research on PSO evacuation problems mainly focuses on simulation, that is, the behavior of particles simulating evacuation individuals, but the application of particle swarm optimization algorithm to There are not many studies on the optimization of the evacuation process. The difficulty is that one evacuation process simulated by PSO is an evacuation plan, and the purpose of the present invention is to obtain a better evacuation plan according to the evacuation goal. Therefore, it is necessary to use particle swarm simulation multiple times to approach the optimal The evolution of the process requires the use of pheromones on the evacuated network; on the other hand, the traditional particle swarm only considers the learning between particles, and ignores the influence of the particle network on the particle movement.

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