A Two-Level Cloud Warehouse Location in Consideration of Total Expected Demand Coverage

The coronavirus disease pandemic and live streaming e-commerce continue to substantially influence e-commerce worldwide, accelerating the transformation and upgrading of warehouses. Cloud warehouses are suitable for the current environment, and applying them in real life is necessary. We proposed a bi-objective and multi-product model for designing a two-level cloud warehouse system in a three-tier supply chain network that combines the total cost and total expected demand coverage calculated by gradual and cooperative coverage. Finally, a real case in China is presented and solved using the lexicographic and augmented ε-constraint (AUGMMECON) methods. To demonstrate the superiority of the proposed model, a model without cloud warehouses was solved using AUGMMECON. We then used the PROMETHEE-II to select the optimal solution and compared the results to show the feasibility of this model and the superiority of AUGMMECON method. This model produces a front of Pareto optimal and efficient solutions for the locations of cloud warehouses and provides decision-makers with a way to select a preferred optimal solution based on their preferences