Abstract Because the first batch of emergency resources cannot meet all the needs from the disaster areas in the initial stage of a large-scale disaster, decision makers should consider both fairness and efficiency. A multi-objective mathematical optimization model with the minimum total weighted envy value as the fairness goal, the minimum total logistics cost as the efficiency goal, and the proportional fairness as constraints is established. An improved fast non-dominated sorting genetic algorithm is proposed to find Pareto frontier of the model, and a Pareto frontier solution selection strategy is presented. The numerical results verify the effectiveness of the model and algorithm, and reveal the trade-off between the minimum envy fairness and the proportional fairness, and show that the degree of shortage of resources objectively determines the overall fairness degree.
