基于计算设计科学，开发并优化算法模型，解决供应链中涉及的采购、生产、销售，物流与库存等复杂运营问题。探索强化学习、图神经网络、预测模型等方法在智能运营中的应用，推动运营效率与可持续发展。

Grounded in computational design science, this research direction focuses on the development and optimization of algorithmic models to address complex decision-making challenges in supply chain management such as purchase, production, sales, logistics, and inventory control. Emphasis is placed on advanced techniques including reinforcement learning, graph neural networks, and predictive analytics, with the aim of enabling intelligent, adaptive, and sustainable operational solutions.

领域：算法设计与优化、数智化供应链、预测建模与强化学习。

Topics : Algorithm design and optimization, intelligent supply chain operations, predictive modeling, and reinforcement learning.