An effective emergency logistics scheduling model based on multi-objective optimization algorithms

Abstract

In recent years, frequent public emergencies have resulted in heavy casualties and economic losses. In the early stage of emergency rescue, the demand for emergency resources is strictly greater than the supply. As an important part of emergency management, emergency resource scheduling is an important manifestation of its rescue value. At present, Many studies take emergency resource scheduling as a multi-objective optimization problem. They focus on the total emergency cost and does not evaluate the emergency resource allocation according to the actual disaster severity of each emergency demand point. What's more, they do not consider road information. However, in actual, the condition of roads directly affects the emergency cost. To address this problem, we proposed an effective emergency logistics scheduling model based on multi-objective optimization algorithms. We get road information from spatial-temporal trajectory data. The research on emergency resource scheduling in this paper is helpful to achieve greater utility under the condition of limited emergency resources and reduce the loss of public emergencies.