A two-echelon stochastic facility location model for humanitarian relief logistics
We develop a two-stage stochastic programming model for a humanitarian relief logistics
problem where decisions are made for pre-and post-disaster rescue centers, the amount of
relief items to be stocked at the pre-disaster rescue centers, the amount of relief item flows at
each echelon, and the amount of relief item shortage. The objective is to minimize the total
cost of facility location, inventory holding, transportation and shortage. The deterministic
equivalent of the model is formulated as a mixed-integer linear programming model and …
problem where decisions are made for pre-and post-disaster rescue centers, the amount of
relief items to be stocked at the pre-disaster rescue centers, the amount of relief item flows at
each echelon, and the amount of relief item shortage. The objective is to minimize the total
cost of facility location, inventory holding, transportation and shortage. The deterministic
equivalent of the model is formulated as a mixed-integer linear programming model and …
Abstract
We develop a two-stage stochastic programming model for a humanitarian relief logistics problem where decisions are made for pre- and post-disaster rescue centers, the amount of relief items to be stocked at the pre-disaster rescue centers, the amount of relief item flows at each echelon, and the amount of relief item shortage. The objective is to minimize the total cost of facility location, inventory holding, transportation and shortage. The deterministic equivalent of the model is formulated as a mixed-integer linear programming model and solved by a heuristic method based on Lagrangean relaxation. Results on randomly generated test instances show that the proposed solution method exhibits good performance up to 25 scenarios. We also validate our model by calculating the value of the stochastic solution and the expected value of perfect information.
Springer