The paper discusses the location-allocation model for logistic networks and distribution centers through considering uncertain parameters. In real-world cases, demands and transshipment costs change over the period of the time. This may lead to large cost deviation in total cost. Scenario based robust optimization approaches are proposed where occurrence probability of each scenario is not known. It is supposed that in this case there would be budget constraints and also holding the products in the distribution centers until sending them to the retailers’ destinations results additive cost that can be defined as inventory control cost in the model. In this paper, uncertainty is defined by different scenarios. Some robust approaches are presented that can be applied in location-allocation problem. The robust scenario based approaches like absolute robust and robust deviation are applied in location-allocation problem. Also a new robust approach is proposed that outperforms the existing classical approaches. The mean expected model has been discussed and compared to the robust proposed approaches. A numerical example illustrates the proposed model and the results have been reported. Finally the comparison of results shows the efficiency of proposed robust approach in comparison of classical approaches and also mean expected model.