Research On The Location And Scheduling Methods Of Multi-resource And Multi-supplier Emergency Problem

In recent years, public emergencies have frequently happened in China, such as natural disasters, terrorist attacks, infectious diseases and so on. These public emergencies have severe influence on the social stability and the people’s life and possession. It is an urgent affair to deal with emergency and improve the emergency management. The core of emergency management is to manage emergency resources. Therefore, based on analyzing the achievement of research, this thesis mainly discussed two important issues in emergency resources management: the emergency-facility location problem and the emergency-resource scheduling problem. Firstly, some basic theories related to emergency management is introduced and the important role of emergency resources management in emergency management is emphasized. Secondly, emergency resource management problem involved in emergency management is analyzed and discussed in detail. Finally, according to above analysis, this paper establishes emergency-facility location model and emergency-resource scheduling model. In addition, the optimization algorithms are developed to solve the models and some numerical examples are given.For multiple emergency-facilities location problem, the paper integrates p-center model, p-median model and covering model to establish a multi-objective decision model, where the objectives are to minimize the cost of facility locations, minimize the maximum distance from facility locations to each emergency demand points and minimize the total weighted distance from facility locations to each emergency demand points. Considering the characteristic of the model, linear weighting method is used to solve the model. In the end a numerical example is given to validate the effectiveness of the method.Under the background of continuous consumption emergency system, a multi-resource and multi-supplier scheduling model, targeting with time cost and transportation cost minimization, is presented under demand restricts, supply restraints and time constraints. According to the characteristic of the model, an improved backtracking search optimization algorithm is put forth, in which the corresponding crossover and mutation operation are discussed in detail to solve and compare the model through simulation example. The simulation result shows the excellent performance of improved backtracking search optimization algorithm. Therefore, the presented model and improved backtracking search optimization algorithm are reasonable and effective.