Abstract: In view of material competition and high cost problems in nonlinear continuous consumption emergency material dispatching, the urgency degree of a demand is confirmed using an improved gray relational method based on combination weighting (which is also used to design the disaster site satisfaction coefficient and lack of material loss coefficient). A multi-objective emergency material dispatching model is established for multiple disaster sites, multiple rescue points, and multiple stages, with an aim of minimizing the total dispatching cost and maximizing multiple disaster sites' satisfaction. In the light of these characteristics of the model, we propose an improved multi-objective particle swarm optimization algorithm based on Pareto dominance. The contrast test of the two models and the contrast test of the two algorithms verified the rationality of the model and the efficiency of the algorithm. Simulation results indicated that the model and algorithm obtained greater satisfaction and lower material dispatching cost, and ensured that disaster sites with higher degree obtained more emergency material and other disaster sites accepted the time delay of material supply.