The Research Of Emergency Logistics System Based On LRP

In recent years, the unexpected events happens frequently which has cause huge impact onour lives, property and social economic growth, so it is necessary to puts forward higherrequirements on the emergency logistics. In view of this, this paper mainly researches onthe location and routing optimization problem of emergency logistics system.Location-routing problems combine the optimal of the location problem and the optimal ofthe path selection problem. And with the development of integrated logistics managementsystem, the LRP problem has gradually been one of the hotspots. So the research onLRP problem has great practical significance. It can not only determine the optimal number ofemergency facilities, location and capacity, but also can arrange the optimal transportationwhich expend the shortest time and the lowest cost. In the emergency logisticssystem, emergency logistics facility location allocation problem and emergencyrescue vehicle routing problem are the two key problems, but these problems are solved inindependent. So in this paper the main works are as following: Firstly analysis ofthe factors of emergency logistics distribution center location in system,establish the standards and systems of emergency logistics distribution center location. Thenestablish the location model of emergency logistics distribution center by the basic ideasof the fuzzy TOPSIS methods. Finally illustrate the fuzzy TOPSIS method through anexample which is an effective way to solve the location problem of emergency logisticsdistribution center. Because when the natural disasters and other major public safety eventshappened, it will increase the security risks of emergency patches, and causesome damages on the emergency path which will lead the rescue vehicle to a certainrandomness on running process and time. So, in this paper, l set the emergency rescue timerequirements as a time window constraint. Therefore establishment a stochasticchance constrained model with time window. In this paper l look the LRP as a whole anddesign the genetic algorithm for LRP, it is implemented by MATLAB, Finally, using anexample to prove the feasibility of this study.