Managing Transshipments in a Multi-Retailer System with Approximate Policies

Using the right transshipment policy is important when transshipments are exercised under demand uncertainty. Optimal transshipment policy can be quite complex in a multi-firm system as optimal actions depend on all system variables. Moreover, both how to select requested retailer and how to respond to requests are in question. We introduce simple, close-to-optimal heuristic transshipment policies for multiple retailers. We first show that heuristic policies may perform even better than self-optimal policy, which is explained by Braess's paradox. Then we test the performances of various heuristics with respect to centrally-optimal policy. When retailers can observe others' inventory levels, more effective transshipments can be made. Otherwise, a random selection performs quite well. We also observe that although always-accept respond policy is quite close to centrally-optimal in small systems, the performance of pairwise-optimal holdback levels to respond requests is more clear and consistent for larger systems