Abstract
In the era of the digital economy, manufacturing service collaboration (MSC) effectively addresses user personalization and customization through networked collaboration among service providers. However, opportunistic negative collaboration behaviors within the network can lead to risk generation, risk propagation and potential dysfunction of the entire collaboration network. Traditional risk control strategies are often based on experience and lack predictive validation. To improve the efficiency of risk control strategy formulation and validate the effectiveness of risk control, the article proposes a negative collaboration risk control optimal strategy exploration method. This method can realize effective optimal decision-making for risk control and effectiveness validation by combining the complex network evolutionary game and Q-learning. The experiment results show that this method is able to formulate situation-specific risk control strategies and keep negative collaboration providers below 10%, effectively controlling MSC risk.
| Original language | English |
|---|---|
| Article number | 125545 |
| Journal | Expert Systems with Applications |
| Volume | 261 |
| DOIs | |
| State | Published - 1 Feb 2025 |
Keywords
- Collaboration behavior
- Manufacturing service collaboration
- Negative collaboration risk
- Risk control
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