Evacuation Route Optimization Of The Bulk Supermarket Fire Based On Improved Ant Colony Algorithm

With the development of economy and society,the number of the bulk supermarkets is growing rapidly.The bulk supermarket integrates commodity sales and commodity storage,with the characteristics of large scale,concentrated goods and large flow of personnel.Fire is one of the main risk factors of the bulk supermarkets,the analysis of the bulk supermarkets fire characteristics,compared with ordinary supermarket fire probability,high degree of danger,and the evacuation conditions are poor and difficult.Therefore,on the basis of fully analyzing the existing research results,this paper combines the advantages of ant colony algorithm to optimize the evacuation path of the bulk supermarkets in case of fire.Based on ant colony algorithm,this paper optimizes the evacuation path of the bulk supermarket fire.Firstly,the traditional ant colony algorithm is improved from two aspects:(1)Analyze the fire characteristics of the bulk supermarkets,analyze the characteristics,classify and quantify the factors affecting evacuation(smoke layer height,CO concentration,temperature,visibility)during fire,and construct a new heuristic function.(2)Adopt adaptive pheromone volatilization rules to solve the problem that ant colony algorithm is easy to fall into local optimum prematurely.With the help of improved ant colony algorithm,according to the characteristics of the bulk supermarket fire,the optimal route is determined according to the development and change of fire under the premise of ensuring the safety of personnel.Secondly,three groups of simulation are set up to verify the feasibility and superiority of the improved ant colony algorithm:(1)The improved ant colony algorithm and the traditional ant colony algorithm are simulated without fire;(2)When the fire occurs for 6min,the path search of the improved ant colony algorithm and the traditional ant colony algorithm is simulated.(3)The different stages of fire development are simulated,and the path search results of the improved ant colony algorithm are obtained when the fire occurs for 10 s,100s and 200 s.By comparing and analyzing the results of three groups of simulation,it is concluded that the improved ant colony algorithm is not easy to fall into the local optimum.It can search out the better path under the premise of ensuring the safety of the evacuees,and can adjust the evacuation path according to the development and change of the fire.Finally,a bulk supermarket was investigated on the spot,different working conditions were set up and Pyro Sim was used to simulate the fire,and the simulation results were substituted into the improved ant colony algorithm.The evacuation model is established by Pathfinder,and the parameters of evacuation in the model are set by the path searched by the algorithm.The evacuation result with the shortest distance is 31.4s,and the evacuation result of the optimized path is 54.5s,55.3s and 30.8s.The evacuation time is within the allowable range of safe evacuation time.Although the optimized path takes longer,a safer evacuation path is selected,and when the evacuation time to the unoptimized path is 31.4s,about three quarters of the total number of people are safely evacuated,and the evacuation effect is better.At the same time,it analyzes and clarifies the implementation process of the dynamic evacuation system of the bulk supermarkets.The ant colony algorithm established in this paper can be used for the evacuation of fire personnel in the bulk supermarkets.Through model simulation and case analysis,it is verified that the improved ant colony algorithm can avoid the fire danger area for path search and overcome the algorithm itself is easy to fall into the local optimal shortcoming,which has feasibility,superiority and practical significance of application.