摘要：This paper aims to address the problem of post-disaster emergency material dispatching from multiple supply points to multiple demand points. In the case of large-scale natural disasters, it is very important for multiple emergency material supply points to serve as the source of material supply for multiple disaster sites and to accurately determine the emergency material scheduling solutions. Moreover, the quantity of emergency materials required for each disaster site is uncertain. To address this issue, in this work, we mainly present an emergency material scheduling model with multiple logistics supply points to multiple demand points based on the grey interval number. Aiming at the multi-supply points and multi-demand points emergency material scheduling model proposed, a multi-objective optimization algorithm based on the genetic algorithm is adopted to optimize the multi-objective scheduling model. The experimental results show that the multi-objective optimization method can solve the emergency logistics scheduling problem better than the particle swarm multi-objective solution algorithm. At the same time, the multi-supply points and multi-demand points emergency material dispatch model and optimization algorithm provide robust support for emergency management system decision-makers when they need to respond quickly to disaster relief activities.
