Prof. Zhigang Lu’s research centers on supply chain networks, complex systems modeling, and intelligent optimization methods, with a strong emphasis on network resilience, partner selection, and information diffusion. The scholarly output comprises 8 indexed documents that have attracted 43 citations from 43 citing works, resulting in an h-index of 4, indicating consistent academic influence. The research portfolio integrates agent-based modeling, multi-objective optimization, community detection, and link prediction to address challenges in electric vehicle supply chains, seaport–dry port networks, carbon-aware logistics, and enterprise cooperation networks. Published in reputable journals such as Expert Systems with Applications, Computers & Industrial Engineering, Systems, Kybernetes, and International Journal of Computational Intelligence Systems, the work advances understanding of cascade failure dynamics, knowledge diffusion, reputation-based decision-making, and hybrid intelligent algorithms. Collectively, these contributions provide robust analytical frameworks and computational methods for enhancing efficiency, resilience, and sustainability in modern supply chain and networked economic systems.