›› 2020, Vol. 32 ›› Issue (2): 299-307.

• 物流与供应链管理 • 上一篇    下一篇

双重不确定信息下双源采购策略研究

韩素敏, 宋华明   

  1. 南京理工大学经济管理学院, 南京 210094
  • 收稿日期:2017-08-09 出版日期:2020-02-29 发布日期:2020-03-07
  • 通讯作者: 宋华明(通讯作者),南京理工大学经济管理学院教授,博士生导师,博士
  • 作者简介:韩素敏,南京理工大学经济管理学院博士研究生。
  • 基金资助:

    国家自然科学基金项目(71172105)。

Dual Sourcing Policy under Bi-level Uncertain Demand Information

Han Sumin, Song Huaming   

  1. School of Economics & Management, NUST, Nanjing 210094
  • Received:2017-08-09 Online:2020-02-29 Published:2020-03-07

摘要:

在产品需求不确定以及需求分布参数不确定的情形下,研究两周期双源采购问题。针对一次采购机会和双源采购分别构建了零售商的决策模型,并进行了最优解的分析与求解。进一步,通过数值算例对一次采购机会、无需求预测更新时的双源采购和需求预测更新下的双源采购三种情形进行了对比。数值分析表明,需求预测更新能够有效帮助零售商把握市场变动,获得更大利润。最后,分析了参数对零售商最优决策和需求预测更新价值的影响。研究结果表明,需求预测更新价值与产品需求的不确定性呈负相关,与需求均值的不确定性呈正相关。此外,当第一次采购价格与库存成本之和与第二次采购价格相差不大,或第二次采购价格相对较小时,需求预测更新能为零售商带来显著效益。

关键词: 双重不确定信息, 双采购源, 两周期需求, 贝叶斯信息更新

Abstract:

In this paper, we investigate the retailer's dual sourcing policy of multi-stage demand. We assume that the demand of the product has two level uncertainty, i.e., the uncertainty of the product requirements and distribution parameters. Models are constructed for one procurement opportunity and dual sourcing procurement respectively. In order to compare the impact of Bayesian information updating, we compare the optimal policies of three different cases. The result shows that Bayesian information updating can help retailers grasp the changes of market and gain more profits. We also discuss the influences of each parameter on the retailer's optimal policy and the value of demand forecast updating. It is found that the value of demand forecast updating is positively related to the uncertainty of the distribution parameters and negatively related to the uncertainty of the product requirements. Another finding is that when the purchasing cost in the second period is not too high, or both the purchasing cost in the second period and the sum of the purchasing cost and inventory cost in the first period are at similar levels, the demand forecast updating is valuable.

Key words: bi-level uncertain demand information, two ordering opportunities, multi-stage demand, Bayesian information updating