School of Management Science and Engineering, Anhui University of Technology, Maanshan 243032, China;School of Management, University of Shanghai for Science and Technology, Shanghai 200093, China 在期刊界中查找 在百度中查找 在本站中查找
In view of the characteristics of traffic networks capacity under the situation of mass emergency, this paper cites the BPR impedance function to solve the vehicle travel time between the various sections. It builds the shortest path and the shortest vehicle scheduling model and designs the improved discrete Glowworm Swarm Optimization Algorithm. It constructs a numerical example to solve the model and the results are compared with the results of genetic algorithm. The feasibility of the algorithm is verified and can better meet the needs of emergency rescue vehicle scheduling.