| 自适应控制对多级库存延迟问题的优化研究 |
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| 引用本文： | 赵川,李璐瑶,杨浩雄,左敏. 自适应控制对多级库存延迟问题的优化研究[J]. 计算机工程与应用, 2022, 58(17): 285-297. DOI: 10.3778/j.issn.1002-8331.2101-0030 |
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| 作者姓名： | 赵川 李璐瑶 杨浩雄 左敏 |
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| 作者单位： | 北京工商大学 电商与物流学院，北京 100048 |
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| 摘 要： | 针对在随机需求下交货延迟所导致供应链多级库存系统库存积压、缺货和牛鞭效应等问题，建立了基于自适应控制算法的多级库存动态优化模型。通过泰勒展开和拉布拉斯变换建立了基于APIOBPCS策略考虑延迟的动态多级库存控制模型；由Lyapunov渐进稳定性定理设计了一种适用于多级库存的模型参考自适应控制算法，其中以无交货延迟的参考库存模型作为目标，通过调节线性补偿函数和自适应控制率，逐渐缩小实际库存模型与参考库存模型间的输出误差，以此削弱交货延迟对多级库存模型的影响；通过实证数据验证了模型参考自适应控制对一个三级供应链库存系统的动态优化效果。仿真结果表明，自适应控制下的无信息共享多级APIOBPCS库存系统缺货全部归零，牛鞭效应下降40.7%。在不增加企业运营投入的前提下，通过自适应控制算法，优化资源配置，动态削弱了交货延迟对多级库存的影响，提升了供应链运营效率。
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| 关 键 词： | 交货延迟 自适应控制 APIOBPCS 动态库存优化 |
Optimization Research on Delay Problem of Multi-Echelon Inventory Based on Adaptive Control |
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| ZHAO Chuan,LI Luyao,YANG Haoxiong,ZUO Min. Optimization Research on Delay Problem of Multi-Echelon Inventory Based on Adaptive Control[J]. Computer Engineering and Applications, 2022, 58(17): 285-297. DOI: 10.3778/j.issn.1002-8331.2101-0030 |
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| Authors: | ZHAO Chuan LI Luyao YANG Haoxiong ZUO Min |
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| Affiliation: | School of E-Business and Logistics, Beijing Technology and Business University, Beijing 100048, China |
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| Abstract: | Considering the problems of inventory overstock, stockout and bullwhip effect caused by random demand fluctuation during the time of delay, a multi-stage inventory dynamic optimization model based on model reference adaptive control（MRAC） is established. Firstly, based on APIOBPCS theory, the multi-stage inventory dynamic model is established by applying Taylor expansion and Laplace transformation. Secondly, based on the Lyapunov asymptotic stability theory, a model reference adaptive controller suitable for multi-stage inventory control is designed. In this MRAC system, a reference inventory model with smaller time of delay is set as the target. By adjusting the linear compensator function, the output error between reference inventory model and actual inventory model is narrowed, and the inventory system achieves dynamic gradual stability. Finally, through numerical simulation, the dynamic optimization of MRAC on a three-stage supply chain inventory system is tested. The simulation results show that the average residual inventory of the multi-stage inventory systems without information sharing under adaptive control decreases slightly, the stockout has completely improved, and the bullwhip effect decreases by 40.7%. Under the premise of not increasing the operation cost, this paper optimizes the resource allocation through the adaptive control algorithm, and most importantly, dynamically weakens the impacts of time of delay on multi-stage inventory and improves the operation efficiency of the whole supply chain. |
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| Keywords: | delivery delay adaptive control APIOBPCS dynamic inventory optimization |
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