Swarm Intelligence Algorithm Research On Mine Fire Rescue Path Optimization With Multiple Rescue Teams

Determining the optimal emergency rescue path is one of the primary tasks to dealwith the mine fire. Optimization of underground fire-rescue path based on multiplerescue teams,with good theoretical significances and application prospects, not onlyprovides evidences for decision-making on planning mine accident rescue path andchoosing the optimal evacuation route for under-ground staff in emergency, but alsobenefits rescue teams for arriving at the accident scene timely, implementing on-sitefirst-aid and rescuing trapped staff safely.The main contents include the following aspects:First of all, the underground fire rescue path optimization model based onmultifactor has been constructed. According to features of the underground mine firedisaster and rescue system, this article clarifies the meaning of the optimal rescue pathand the optimal edging path. In this article, the Rescue path has been described, startsfrom the ground relief workers entering into the main shaft or air shaft, passes thoughall of hazardous roadway, ends with rescuing all of the trapped stuff in undergroundwells and returning to the main shaft or air shaft. According to classifying theunderground tunnel and analyzing each factor, this article calculates the accessibledifficulty coefficients and the equivalent length of rescue path, and successfully buildthe network model of rescue path and the underground fire rescue path optimizationmodel.Next, swarm intelligence algorithm research on mine fire rescue path optimizationmodel is studied in this paper,By analyzing and comparing the traditional routeoptimization algorithm (Dijkstra algorithm, A*algorithm, Floyd algorithm) to the Swarm intelligence algorithm, the article comes to the advantages and disadvantages ofswarm intelligence algorithm. It describes the basic theory, mathematical description,parameter analysis and algorithm flow of a hybrid algorithm which mixes the theparticle swarm algorithm and the ant colony algorithm and aims to calculate theunderground fire rescue path optimization model.Again, this paper brings out a hybrid algorithm, that based on merits of PSO andACO-using PSO searched parameters α、β、ρ ofACO,then backed to ACO and searchedfor optimal rescue path of multiple rescue teams. Meanwhile,this article describes theMATLAB implementation steps of using particle swarm algorithm to search α、β、ρ andcalculating the rescue path by ant colony algorithm and specific processes andprocedures of the swarm intelligence algorithm.At last, this pape takes the Longtougou gold mine underground mine fire rescuepath as an example. the optimization of underground fire-rescue path explored in thispaper will provide scientific basis for decision-making to deal with mine undergroundfire.This article proposes the hybrid algorithm which mixes the particle swarmalgorithm and the ant colony algorithm can quickly and efficiently search the optimalunderground fire emergency rescue path, help rescue team safely and quickly to reachthe location of trapped stuff in underground tunnel and timely rescuing them. Aboveall,the research described in this article has a application value.