Abstract:

In order to solve the problem of post-disaster emergency material supply, this paper was targeted at the multi-modal transport mode of truck-aircraft-truck, and the four-layer emergency service network consisting of "material suppliers, transfer stations, distribution center, and demand points" in view of the urgency of emergency needs and the layer-by-layer transportation mode in real logistics operation. A multi-objective mixed integer dynamic program was established with the objectives of minimizing total system operational cost, total transportation time and truck drivers' psychological cost from the perspective of the government, disaster victims and drivers involved in emergency transportation, respectively. The Epsilon constraint algorithm was adopted to solve the model, and a sensitivity analysis was given to test the performance of some key parameters. The results of the case study show that the model can obtain a set of effective nondominated solutions, i.e., Pareto frontier, which can provide helpful multi-stage emergency supply plans with different decision preferences. A longer or shorter operation time in the transfer stations will increase the total emergency response time. The total cost of the system will not move monotonously with the change in the driver's psychological limit driving time.

Key words: multi-modal transportation, emergency material supply, multi-objective optimization, driver's psychology, Epsilon constraint method