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Researchers from ISyE Partner with China’s SF Express on Data-driven Design of Logistics Networks

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As Shenzhen continues to rapidly grow and evolve as the high-tech hub of China, companies are looking for ways to improve their supply chains and logistics. In order to address challenges and expand opportunities, researchers from Georgia Tech’s H. Milton Stewart School of Industrial and Systems Engineering (ISyE) are partnering with SF Express, the largest Chinese express delivery and logistics service provider headquartered in Shenzhen. 

Led by ISyE’s Benoit Montreuil, Coca-Cola Material Handling & Distribution Chair and professor, director of the Physical Internet Center, and co-director of the Supply Chain & Logistics Institute (SCL), the research team includes James C. Edenfield Chair and Professor and SCL co-director Martin Savelsbergh; Schneider National Chair in Transportation and Logistics and Professor Chip White; Associate Chair for Graduate Studies and Coca-Cola Professor Alan Erera; David M. McKenney Family Early Career Professor and Associate Director of the Center for Machine Learning Sebastian Pokutta; Leo and Louise Benatar Early Career Professor Alejandro Toriello; and A. Russell Chandler III Early Career Professor George Lan; and engages dozens of graduate student researchers. 

Shenzhen is China’s fastest growing high-tech megacity. Considered the Silicon Valley of China, the city sits on the Pearl River Delta and borders Hong Kong. With a population of 18 million people, Shenzhen has the highest gross domestic product per capita among medium and large Chinese cities. The Shenzhen port is the third largest container port in the world.

In 2017, ISyE researchers traveled to Shenzhen where they met with representatives from SF Express, the largest logistics company in China, to discuss partnership opportunities. The discussions led to the co-development of several multi-year research projects, some of which will focus on the data-driven design and operation of both inter-city and intra-city logistics service networks, as well as the design and operation of smart hyperconnected fresh supply chain solutions.  

The smart hyperconnected intra-city and inter-city logistics service network projects center on enhancing delivery performance, respectively between cities across China and within China’s megacities. Both projects aim to enable expanding coverage, enhancing service, and improving speed efficiency, cost-effectiveness, agility, sustainability, and resilience.  Both favor a data-driven approach adapted to the cultural, economic, demographic, and geographic reality of China and its global connectivity. They will establish models and methods for designing flexible service network configurations and operating those configurations efficiently and cost-effectively, which will, in turn, be assessed, improved, and enhanced after initial implementation. 

As SF Express invests in developing end-to-end supply chain for delivering fresh products, the hyperconnected fresh supply chain project builds on the smart intra-city and inter-city logistics systems projects currently underway. This project will lead to the development of the framework and methodologies for designing and operating smart hyperconnected fresh product supply chain solutions. The project will support SF Express in pilot testing the overall concept and approach for targeted fresh products. 

All projects will draw on machine learning, optimization, simulation, and systems design methodologies, and will use Physical Internet concepts and principles to design hyperconnected logistics networks and supply chain solutions.

Describing the impact of the partnership with SF Express, Montreuil said, “This is a tremendous opportunity for the faculty and students involved, and strategically positions Georgia Tech, ISyE, SCL, and the Physical Internet Center in China, advancing our position at the forefront of smart city, Physical Internet, and logistics innovation across the world.”

Status

  • Workflow Status:Published
  • Created By:Andy Haleblian
  • Created:05/29/2018
  • Modified By:Shelley Wunder-Smith
  • Modified:06/06/2018