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运筹学学报(中英文) ›› 2026, Vol. 30 ›› Issue (2): 149-158.doi: 10.15960/j.cnki.issn.1007-6093.2026.02.011

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参数值未知情况下获取库存系统最优订货量——考虑库存依赖型需求率

郭战兵, 张业杰   

  1. 河北工业大学经济管理学院, 天津 300401
  • 收稿日期:2024-09-05 出版日期:2026-06-15 发布日期:2026-06-12
  • 通讯作者: 郭战兵 E-mail:zhanbingguo@hebut.edu.cn
  • 基金资助:
    国家自然科学基金 (No. 72002065)

Solving the optimal order quantity for an inventory system with unknown parameter values——Based on stock-dependent demand rate

GUO Zhanbing, ZHANG Yejie   

  1. College of Economics and Management, Hebei University of Technology, Tianjin 300401, China
  • Received:2024-09-05 Online:2026-06-15 Published:2026-06-12

摘要: 针对库存管理中模型参数值难以准确获知的困难,为需求率依赖于库存水平的库存系统提供了一种可以获得最优订货量的两阶段订货策略。该订货策略通过构建动态订货量并分析其相关性质,实现控制参数临界值的估计和最优订货量的获得。该两阶段订货策略既借鉴了经典EOQ模型中简单的数学形式,又不需要零售商提前获知精确的模型参数值,理论分析和数值模拟表明该策略是可行的。敏感性分析进一步给出了控制参数临界值的估计误差对该策略有效性的影响,结果表明该两阶段订货策略对控制参数临界值的误估计具有较好的鲁棒性。

关键词: 库存管理, 参数值未知, 库存依赖型需求率, 适应性EOQ

Abstract: Considering the difficulty in obtaining the accurate parameter values in the inventory models, this paper provides a two-stage ordering strategy for one kind of inventory system, where the demand rate depends on the inventory level. By constructing a dynamic order quantity and analyzing its related properties, this two-stage order strategy realizes the estimation of critical value for control parameter, and finally obtains the optimal order quantity. Moreover, this two-stage ordering strategy not only draws on the simple mathematical form of the classic EOQ model, but also does not require the retailer to know the exact model parameter values in advance. Theoretical analysis and numerical simulation demonstrate the feasibility of this strategy. Sensitivity analysis further provides the impact of the estimation error of the control parameter critical value on the effectiveness of this strategy, and the results show that this two-stage ordering strategy is robust to the misestimation of critical value for control parameter.

Key words: inventory management, unknown parameter value, stock-dependent demand rate, adaptive EOQ

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