Multi-tank joint replenishment problem with overlapping time windows in refined oil distribution

The refined oil distribution provides energy security for residential consumption and economic operation. The unified replenishment of multiple tanks in a gasoline station is likely to result in single tank stock-outs, while replenishment of individual tanks can lead to high distribution costs. To balance these two contradictory issues, this study considers the overlapping time windows of multiple tanks at gasoline stations and conducts a strategy of distribution replenishment. Firstly, a detailed mechanism explanation of the multi-tank joint replenishment strategy with the overlapping time windows is provided. Based on the multi-tank joint replenishment problem, a refined oil distribution model is proposed, and the one-time replenishment of multiple tanks in a gasoline station is achieved by minimizing the total cost. Next, a differential evolution algorithm with generalized opposition-based learning (GOBL-DE) algorithm is developed to solve this distribution model by combining the advantages of opposition-based learning in quick convergence and DE in population diversity. Finally, a case study was conducted with the Guangdong sales company in China, where five consecutive cycles of replenishment were carried out. The results show that the distribution model with joint replenishment proposed in this paper can effectively prevent single tank stock-outs and reduce distribution costs. The replenishment of each cycle increases the time window overlap by 17.92%, significantly improving distribution efficiency. In addition, comparative analysis of the algorithm indicates that the GOBL-DE is a significant improvement about 12.23% on the classical heuristic algorithm and 13.57% on other improved algorithms due to its good convergence and search capability, which shows superiority in solving the distribution model with joint replenishment strategy. Therefore, applying the multi-tank joint replenishment strategy to the refined oil distribution network and offers the possibility of increased efficiency and reduced costs.