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A constrained EPSAC approach to inventory control for a benchmark supply chain system

机译:基准供应链系统的约束EPSAC库存控制方法

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The design of an appropriate inventory control policy for a supply chain (SC) plays an essential role in tempering inventory instability and bullwhip effect. Several constraints are commonly encountered in actual operations so managers are required to take these physical restrictions into account when designing the inventory control policy. Model predictive control (MPC) appears as a promising solution to this issue, due to its capability of finding optimal control actions for a constrained SC system. Therefore, the inventory control problem for a benchmark SC is solved using the extended prediction self-adaptive control approach to MPC. To extend methodologies in our previous work, the control framework relies on generic process model and incorporates the physical constraints arising from practical operations to form the general constrained optimisation problems. The managers can choose from decentralised and centralised control structures according to specific informational and organisational factors of their SCs. The proposed control schemes in this study may be appropriate for industrial practice because the designed policy can bring a reduction of over 30% in operating cost and a significant increase of customer satisfaction level compared with that of the conventional policy.
机译:为供应链(SC)设计适当的库存控制策略在控制库存的不稳定性和牛鞭效应中起着至关重要的作用。在实际操作中通常会遇到一些限制,因此在设计库存控制策略时,要求管理人员考虑这些物理限制。由于模型预测控制(MPC)能够找到约束SC系统的最佳控制动作,因此它有望作为解决该问题的方法。因此,使用MPC的扩展预测自适应控制方法可以解决基准SC的库存控制问题。为了扩展我们先前工作中的方法,控制框架依赖于通用过程模型,并结合了实际操作中产生的物理约束,从而形成了一般约束优化问题。管理者可以根据SC的特定信息和组织因素从分散和集中控制结构中进行选择。本研究中建议的控制方案可能适合于工业实践,因为与传统策略相比,设计策略可以减少30%以上的运营成本并显着提高客户满意度。

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