Research on Bullwhip Effect under Supplier Interruption Risk Based on Sliding Mode Predictive Control

Supply chain disruptions, such as natural disasters, equipment failures, poor inventory management, worker strikes, and financial issues, can amplify demand fluctuations, known as the bullwhip effect, affecting supply chain stability. This paper explores the application of Sliding Mode Predictive Control (SMPC) to mitigate the bullwhip effect in the context of supplier disruptions. First, a dynamic multi-level supply chain model is constructed, covering inventory and order quantities at each node, considering demand fluctuations and disruption risks. Then, a sliding mode control strategy is designed, using an error sliding surface combined with a sign function and control gain to achieve real-time adjustment of order quantities. By integrating a predictive control model, the strategy optimizes short-term control inputs to reduce the impact of demand fluctuations. Simulation results demonstrate that sliding mode predictive control effectively reduces the bullwhip effect and enhances supply chain robustness and stability.

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Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/spic62469.2024.10691447
Primary Topic
Elevator Systems and Control
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on Bullwhip Effect under Supplier Interruption Risk Based on Sliding Mode Predictive Control

Zhenglin Yao, Hai-Feng Guo, Xiao Zhang
Elevator Systems and Control
article

Research on Bullwhip Effect under Supplier Interruption Risk Based on Sliding Mode Predictive Control

Zhenglin Yao, Hai-Feng Guo, Xiao Zhang
article en

Abstract

Supply chain disruptions, such as natural disasters, equipment failures, poor inventory management, worker strikes, and financial issues, can amplify demand fluctuations, known as the bullwhip effect, affecting supply chain stability. This paper explores the application of Sliding Mode Predictive Control (SMPC) to mitigate the bullwhip effect in the context of supplier disruptions. First, a dynamic multi-level supply chain model is constructed, covering inventory and order quantities at each node, considering demand fluctuations and disruption risks. Then, a sliding mode control strategy is designed, using an error sliding surface combined with a sign function and control gain to achieve real-time adjustment of order quantities. By integrating a predictive control model, the strategy optimizes short-term control inputs to reduce the impact of demand fluctuations. Simulation results demonstrate that sliding mode predictive control effectively reduces the bullwhip effect and enhances supply chain robustness and stability.

Shenyang Ligong University (CN)
Climate action
Openalex Percentile: Top 81%
Elevator Systems and Control
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