Yongxiang Li

Guizhou University, South China University of Technology

Papers

Total Citations

H-Index

About

Yongxiang Li is a leading researcher in cloud manufacturing and intelligent optimization, whose work addresses critical challenges in modern supply chain resilience and service composition. His most influential paper, "Cloud Manufacturing Service Composition Optimization with Improved Genetic Algorithm" (2019, 22 citations), tackles the complex multi-objective problem of selecting and combining cloud services for manufacturing tasks. Li introduced a novel approach that accounts for synergy between composite services—a factor often overlooked—and reduces composition complexity, enabling more efficient and effective manufacturing networks. Building on this foundation, his 2024 study (5 citations) develops an improved Chaos Sparrow Search Algorithm that incorporates time-varying reliability and credibility evaluations, directly responding to global economic and political disruptions that threaten multinational supply chains. By integrating manufacturing entity reliability and service reputation into the optimization process, Li provides a robust framework for maintaining production continuity under uncertainty. His work is widely cited by researchers in industrial engineering and operations research, and it has practical implications for firms seeking to build trustworthy, adaptive manufacturing ecosystems. Li’s contributions are essential reading for anyone studying service-oriented manufacturing, supply chain risk management, or nature-inspired optimization algorithms.