a locating model for small e-shop distribution centers in conditions of uncertainty

In today’s world, due to the competitive nature of the market and the lack of certainty in the amount of order and also the time of ordering products, it has led to the effective response of sales centers to customers is not done properly. this is due to the lack of proper location of distribution and sales centers and optimal allocation of customers to each center. therefore, considering the importance of locating distribution centers, in this article, the issue of locating distribution centers of e-shops in conditions of uncertainty has been developed. the main purpose is to provide a model for profit maximization and minimization of the total transfer time of electronic products between distribution centers and customer clusters. to examine the developed model, three different problem solving methods have been considered, including the epsilon constraint method, the nsga ii algorithm and the mopso. the results obtained from the analysis of the sample problem in small size show that nsga ii algorithm has 14 efficient answers, mopso algorithm has 10 efficient answers and epsilon method has obtained a limit of 8 efficient answers. the computational results show the high efficiency of the mopso algorithm in obtaining the optimal weight of 0.9744 in solving large size problems.