零售价波动销售策略下的报童模型研究

价格波动销售策略普遍存在于各种买卖活动中，并导致了需求的不确定性使得零售商更容易发生供应不足或供过于求的现象，因此，价格波动时的订购问题更为重要.本文研究零售价波动且需求不确定的一次性订货问题.以期望损失最小为目标，建立订货模型，通过对价格区间的划分导出了最优订购量的近似表达式.理论上证明了价格区间划分方法的收敛性和解的存在性，并给出了在有限样本下的求解算法.根据实际销售数据进行了数值实验，证实了所提出的模型可以得到近似最优订购量.实验结果表明采用价格波动模型所得到的期望损失小于传统价格确定报童模型所得的期望损失，价格波动均值以及需求方差的变动会引起最优订购量的明显改变.

Research on newsvendor model under retail price fluctuation sales strategy

Price fluctuation sales is popular in lots of trading activities, which may lead to uncertainty of demand, making retailers more likely to suffer from understock or overstock. Thus, the ordering problem is important when price fluctuation occurs. This paper studies one-period ordering problem when retail prices fluctuate with uncertain demand. An optimization model is established aiming at minimizing expected loss. By adopting price interval partition, an approximate solution is derived. The convergence and existence of the solution are theoretically proved, and the solution algorithm is given in the case of finite samples. Numerical experiments are carried out showing that the expected losses caused by price fluctuation is much more lower through the proposed model as compared to that in traditional newsvendor model. The mean value of retail prices and the deviation of demand have some effect on the optimal ordering quantity.