Solving the Tasks Dynamic Allocation Problem via Discrete Adaptive GMRA in the Supply Chain

The rapid expansion of the new energy vehicle market has attracted a significant number of enterprises to join the industrial chain. To enhance competitiveness, automakers must strategically select suppliers. However, long-term cooperation with a single supplier can lead to over-reliance, thereby increasing supply chain risks and the potential for quality degradation. Consequently, dynamically managing suppliers to ensure both flexibility and stability has emerged as a critical challenge. This paper formalizes the tasks dynamic allocation problem in the supply chain using the Discrete Adaptive Group Multi-Role Assignment (GMRA) model. It introduces two conservative strategies aimed at mitigating the risk of over-reliance on any single supplier. Specifically, it adopts an LRU-inspired mechanism that prioritizes task allocation duration as a key factor and intervenes in the GMRA process via the Qualification matrix. The experimental results examine the impact of different strategies on overall performance and stability, providing a quantitative analysis of the trade-offs between enhanced stability and performance.