工业工程

工业工程 ›› 2024, Vol. 27 ›› Issue (3): 98-105.doi: 10.3969/j.issn.1007-7375.230043

• 智能制造系统与车间调度优化 • 上一篇    下一篇

随机情景下MTS/MTO串联生产系统库存控制策略

林兵1, 冯毅2   

  1. 1. 江苏师范大学 商学院，江苏 徐州 221116;
    2. 电子科技大学 经济与管理学院，四川 成都 610054
  • 收稿日期:2023-03-07 发布日期:2024-07-12
  • 通讯作者: 冯毅 (1970—)，男，四川省人，副教授，博士，主要研究方向为供应链管理。Email：fengyi@uestc.edu.cn E-mail:fengyi@uestc.edu.cn
  • 作者简介:林兵(1969—)，男，江苏省人，副教授，博士，主要研究方向为生产运作管理、物流与供应链管理
  • 基金资助:
    国家社会科学基金资助项目 (19BGL100)

An Inventory Control Strategy for MTS/MTO Tandem Production Systems in Stochastic Scenarios

LIN Bing1, FENG Yi2   

  1. 1. Business School, Jiangsu Normal University, Xuzhou 221116, China;
    2. School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 610054, China
  • Received:2023-03-07 Published:2024-07-12

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摘要： 该研究探讨供应链库存控制策略及生产协同重要性。将备货型生产 (make-to-stock, MTS) 与按订单生产 (make-to-order, MTO) 两级串联模式应用于高效响应性供应链的生产与库存联合控制问题并刻画其最优策略。针对订单到达服从泊松过程和生产时间服从指数分布情形，通过马尔科夫过程转移速率一致化技术建立起马尔科夫决策过程模型并得到相应贝尔曼最优方程。基于最优费用函数结构性质，将最优生产与库存控制策略刻画为依赖系统状态的基本库存策略。随后，将模型拓展到批量生产情形。数值算例验证了最优策略单调结构性质，给出不同情境下的最优策略绩效。同时将最优策略与两种常见策略进行比较。基础情境下，容限策略偏离最优7.36%，短视策略偏离最优25.73%。其他情境下，最优策略都明显优于另两种策略。

关键词: 供应链, 串联生产系统, 库存控制, 马尔科夫决策过程, 最优策略

Abstract: This paper investigates inventory control strategies and the importance of production coordination in supply chains. We apply the two-stage tandem production mode of make-to-stock (MTS) and make-to-order (MTO) to the joint production and inventory control in efficient and responsive supply chains. Also, the optimal strategy is characterized. In cases where order arrivals follow a Poisson distribution and production time follows an exponential distribution, through the technique of rate uniformization for Markov process transitions, we formulate a Markov decision process (MDP) model and derive the corresponding Bellman optimality equation. Then, based on the structural properties of the optimal cost function, we characterize the optimal production and inventory control strategies as a basic inventory strategy dependent on system states. Subsequently, the model is extended for cases of batch production. Numerical examples verify the monotone structural property of the optimal strategy and further provide the system performance using the optimal strategy. In addition, we compare the optimal strategy with two other commonly used ones. In the baseline scenario, the capacity limit strategy deviates from the optimal one by 7.36%, while the myopic strategy deviates from the optimal one by 25.73%. In other scenarios, the optimal strategy remarkably outperforms the other two strategies.

Key words: supply chain, tandem production system, inventory control, Markov decision process, optimal policy

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