Research On The Particle Swarm Optimization Algorithm Merged With Ant Colony Optimization Algorithm And Its Practice In The Fire And Rescue Path Planning Problem

Fire hazard is serious.The probability of its occurrence is rising with the development of society.Only gradually improve fire rescue work,fire accident casualty rate will decline.Timeliness is the key factor that affects the fire rescue work,and the time that fire fighting vehicle arrives at the scene is closely related to the path chosen.Therefore,how to reasonably select the rescue path to shorten the rescue vehicle arrived at the fire scene is the emergency rescue command center timely and effective rescue work guarantee,is the most important fire rescue action.This paper mainly studies:1)Optimize the path planning with the timeliness as the starting point,combined with the characteristics of the fire rescue path,using the analytic hierarchy process of fuzzy mathematics to evaluate the weight of the road,establish the fire fighting rescue model.2)Analysis of the deficiency of the APSO particle swarm optimization(pso)algorithm,propose a DP-APSO algorithm based on the strategy of DP,implements the population size,inertia weight and learning factor can adaptively adjust the size in the search process,avoid the algorithm falls into local optimum.3)Put forward a new path to the rules of transfer probability and the pheromone update mechanism for optimization of ant colony algorithm convergence problem,and convergence of DP-APSO algorithm,will get the DP-APSO time optimal solution as the initial pheromone distribution of ant colony algorithm incremental,further reducing the search time of the algorithm.Based on the above research,Firstly,the optimization model of rescue path is established by analyzing the characteristics of rescue path planning model after fire.Then according to the actual characteristics of the road,will be solved each path weight matrix is introduced into the particle swarm ant colony algorithm to solve the model of state transition probability,then use this improved state transition rules,and consider the traffic speed to obtaine the optimal path of the model.Finally,the experimental results show that the research content of this paper has certain reference significance for the actual fire rescue dispatching decision.