Study On Emergency Service Facility Location Problem

With the rapid development of modern society, all kinds of emergency happen occasionally. Especially the expediting urbanization causes population and economics centralized highly. The damage of all kinds of emergency become seriously. The research of emergency system is paid more attention by many scholars so as to minimize the damage of various disasters to human. Location decision for emergency facility is very significant to emergency system, which is the premise of that emergency system provides timely and effective service for emergency nodes.Based on the review of former research, as well as considering the actual situation and characteristics of emergency, the paper establishes the model of emergency location and puts the corresponding algorithms.Firstly, the classical emergency location problem often regards on the premise of satisfying the emergency systems' given time (or distance) to cover emergency nodes, but doesn't regard to the satisfaction degree of emergency nodes. In the thesis, we set up maximal covering location model of emergency location problem based on time satisfaction degree. In the light of this situation, we provide the hybrid particle swarm optimization in order to solve the problem. As a result of solving an example, the hybrid particle swarm optimization gets better anticipative solution than greedy add algorithm, the time-satisfaction-based maximal covering location model can cover more emergency nodes than the time-based maximal covering location model.Secondly, with the development of urbanization, emergency service facility should be changed correspondingly. The multi-facility dynamic set covering model was set up. It not only meets the need of the emergency nodes in different steps, but also minimizes the total cost of the whole planning period. We also solve the dynamic problem with combining neighborhood search and ant colony optimization, the experiment results indicate that the method gets better anticipative solution than ant colony optimization.Finally, we set up a hierarchical set covering location model in light of every emergency node demands different higher-lower level facility. And we solve the problem by the hybrid particle swarm optimization. The experiment results indicate that the algorithm will get the anticipative solution in a short time.