Research On Emergency Supplies Replenishment For Safety Houses In Alpine National Park

In 2019,China Tibet officially launched the construction of the Earth's third polar national park cluster,driving the green development of tourism and other industries.Natural disasters are frequent in alternative areas of national park cluster.In the event of an emergency in the highlands that affects human safety,the intensity and speed of the emergency response level is directly related to life safety.In view of the vast and sparsely populated area of China Tibet,it is impossible to ensure timely organization of rescue forces and deployment of emergency supplies.A number of safety houses can be deployed in parts of the national park to store emergency supplies such as food,warmth and medical care,which guide tourists in distress to rescue themselves or take refuge and wait for the emergency services.The communication infrastructure of the national park group is weak,and it is impossible to use low-cost means to check the actual consumption and surplus of emergency supplies of various safety houses.In this thesis,triangular fuzzy number is used to describe the uncertainty of safe house demand,and multiple fuzzy demand point emergency supplies replenishment optimization problem is extracted.Considering the emergency material supply is expanded from a single fuzzy demand point to multiple fuzzy demand points,it is necessary to deal with the uncertainty of the number of demand points when optimizing the optimal transportation volume and to increase the optimization goal of the transportation route.In given route,the fuzzy chance constrained model is established for all situations under different strategies and number of safe houses satisfied to optimize first amount of emergency supplies.Then open the route and embed fuzzy chance-constrained programming in the fitness calculation of the genetic algorithm which transform the path optimization problem into a deterministic classic VRP problem.Through genetic algorithm to find the best transportation route and the corresponding first amount of emergency supplies.Finally,this thesis designs multiple fuzzy demand point examples with Selincuo National Park as the background.Under the three parameters of low,normal and high no-load cost at a fixed path,the effectiveness of solving the enumeration situation by fuzzy chance-constrained programming is verified by the change trend of the corresponding transportation cost,situation and first amount of emergency supplies.In open path,the downward trend of transportation costs also verify the effectiveness of the hybrid genetic algorithm.