Abstract: Location-inventory problem and risk pooling strategy are both very common in logistics network. And location-inventory with risk pooling has obtained the attention of some researchers. Inspired by their research, in this paper, six risk-pooling strategies are combined with traditional location-inventory model and six new location-inventory models with risk pooling are built in a two-echelon logistics network. First, six different risk-pooling strategies are introduced. Risk pooling strategy is composed by safety stock policy and transshipment policy. In two-echelon logistics network, the safety stock could set at upstream regional distribution center or downstream frontier distribution center considering two segments lead time separately or both. As the lateral transshipments will happen when the safety stock is set intensively, then the transshipment cost should be considered in the model with centralized safety stock setting policy. So, the main differences of these models are that they have different safety inventory cost function and different transshipment cost function. However, these different risk pooling strategies could also affect the location and allocation decision indirectly. As the models with risk pooling strategies are non-convex, and they are hard to solve, a genetic heuristic algorithm is proposed. In the genetic heuristic algorithm, the genetic part is set to search the location and the heuristic part is set to do the allocation procedure. Finally, a numerical experimental is presented to prove the validity of our algorithms and models. The results prove both our models and algorithms have good performance. They also show that risk pooling strategy really has great impact on the location-inventory decision. And this impact mechanism related to two important trade-off pairs: 1) safety stock cost and transshipment cost; 2) safety stock cost or transshipment cost and total cost. Furthermore, the trade-off between safety stock cost or transshipment cost and total cost are depend on the ratio of unit cost of safety stock and transshipment. And the threshold value of this ratio is decided by all the other inputs of the model.

Key words: location-inventory, risk pooling strategy, lateral transshipment, genetic algorithm