Route optimization method for emergency vehicles considering demand urgency

Abstract:

For the improvement of emergency management, the degree of material demand for different disaster-stricken sites was quantified, and an optimal route planning method for vehicles was proposed considering the urgency of demand. The K-means clustering algorithm was utilized to determine the selection of emergency material distribution centers and the division of disaster-affected points. With the shortest total time in the emergency rescue process, the minimum total cost of the rescue, and the maximum urgency ranking index of the disaster-affected points as the goal, a multi-objective emergency vehicle routing optimization model was established, and an improved cuckoo-ant colony hybrid algorithm was designed to solve it. Taking the Wenchuan earthquake as the background, the effectiveness of the proposed model was verified. Results show that compared with the vehicle routing scheme without considering demand urgency, the routing optimization scheme considering demand urgency increased the urgency ranking index by 11.2% on the premise that the total transportation time and the total cost of rescue process increased by 1.92% and 3.43%. The vehicle routing optimization model considering the urgency of demand not only ensures the rescue efficiency of sudden disasters, but also considers the material demand degree of different disasters-affected points, and improves the fairness of emergency material transportation.