Dr. Yonglin Ren is a distinguished Senior Project Engineer and Researcher at Concordia University, recognized for his interdisciplinary expertise in mathematical modeling, logistics optimization, and sustainable engineering systems. His research bridges theoretical optimization frameworks and industrial applications, focusing on metaheuristic algorithms, CAD/CAE-based modeling, and supply chain design for humanitarian and sustainable logistics. Dr. Ren’s contributions have advanced methodologies for capacitated location allocation problems, high-speed rail freight transport, and dynamic mechanical system modeling. His work integrates computational intelligence with real-world challenges in water resource management, transportation networks, and crisis logistics, making a significant impact in both academia and industry. His publications are widely cited, reflecting his influence in the fields of operational research and applied optimization, with a Scopus record of 3 indexed documents, 6 citations, and an h-index of 1, alongside a Google Scholar citation count of 26. Dr. Ren has collaborated on multiple international engineering and research projects, driving innovations that contribute to sustainable development and global resource optimization.
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Scopus
Featured Publications
Ren, Y., & Awasthi, A. (2014). Investigating metaheuristics applications for capacitated location allocation problem on logistics networks. Chaos Modeling and Control Systems Design, 213–238.
Ren, Y., & Awasthi, A. (2012). Location allocation planning of logistics depots using genetic algorithm. Research in Logistics & Production, 2, 247–257.
Ren, Y. (2011). Metaheuristics for multiobjective capacitated location allocation on logistics networks. Concordia University.
Ren, Y., Hajiebrahimi, S., Azad, M., Awasthi, A., & Salah, S. (2020). Humanitarian aid for Wuhan with crisis logistics management approach. Proceedings of the International Conference on Industrial Engineering and Operations Management.
Ren, Y., & Awasthi, A. (2025). Logistics hub location for high-speed rail freight transport—Case Ottawa–Quebec City corridor. Logistics, 9(4), 158.