关键词:

转运, 在途库存, 需求预测, 近似动态规划

Abstract:

The real-time transshipment problem of in-transit inventory in replenishment management systems of gas stations needs to consider not only transshipment time and uncertain future demand but also real-time response to transshipment demand. In response to this problem, with the goal of maximizing the overall profit of the remaining decision time period, this paper proposes a method to divide the overall profit into two parts by combining the demand forecasting model and the stochastic demand distribution. First, the remaining decision time period is divided into two parts. Then, the demand for the first period is quantified according to the demand forecasting model, and the total profit for this period and the inventory level at the beginning of the second period are determined. Next, the uncertainty of the demand is measured using the stochastic distribution, and the value function of the inventory level is solved based on the approximate dynamic programming algorithm to measure the total profit of the second period. Afterwards, the selection rule of stations where some in-transit inventory can be transshipped is designed, which can reduce the decision space and improve the response efficiency of the strategy. Finally, the comparative experiment verifies the effectiveness of the transshipment strategies generated by the proposed method under different station sizes and initial inventory ranges, as well as obtains the managerial implications. This paper can provide decision-making support for the real-time transshipment of in-transit inventory in the replenishment management system of gas stations, and enlighten significance for similar real-time transshipment problems that need to consider both transshipment time and future demand.

Key words:

transshipment, in-transit inventory, demand forecasting, approximate dynamic programming