Emergency Logistics Facilities Location Dual-Objective Modeling in Uncertain Environments

Abstract

The uncertainty of post-earthquake disaster situations can affect the efficiency of rescue site selection, material, and personnel dispatching, as well as the sustainability of related resources. It is crucial for decision-makers to make decisions to mitigate risks. This paper first presents a dual-objective model for locating emergency logistics facilities, taking into account location costs, human resource scheduling costs, transportation time, and uncertainties in demand and road conditions. Then, stochastic programming and robust optimization methods are utilized to cater to decision-makers with varying risk preferences. A risk-preference-based stochastic programming model is introduced to handle the potential risks of extreme disasters. Additionally, robust models are constructed for two uncertain environments. Finally, the study uses the Wenchuan earthquake as a case study for the pre-locating of emergency logistics facilities and innovatively compares the differences in the effects of models constructed using different uncertainty methods. Experimental results indicate that changes in weight coefficients and unit transportation costs significantly impact the objective function. This paper suggests that decision-makers should balance cost and rescue efficiency by choosing appropriate weight coefficients according to the rescue stage. It also shows that risk level and robust conservatism can significantly alter the objective function. While stochastic programming models offer economic advantages, robust optimization provides better robustness.