Mr. JIANHUI DU, Sichuan university, China.
My academic and professional journey has been shaped by a strong foundation in logistics engineering, global research collaborations, and impactful contributions to optimization and artificial intelligence-driven methodologies. From earning prestigious scholarships to publishing influential research, my work has consistently aimed at advancing logistics systems in both industrial and humanitarian contexts. As I move forward, I look forward to further pioneering research and innovative solutions that will continue to shape the future of logistics and transportation.
Profile
Orcid
Early Academic Pursuits: Laying the Foundation
My journey into the world of logistics engineering began at Guangzhou Maritime Institute, where I pursued my Bachelor’s degree in Logistics Engineering within the Department of Port and Shipping Management. Graduating in 2018, I was honored with the prestigious Xian Jianbing Scholarship, which strengthened my passion for research and academic excellence. My interest in logistics systems deepened as I moved to the University of Shanghai for Science and Technology, where I earned my Master’s degree in Logistics Engineering from the Business School. During this time, I was recognized as one of Shanghai’s Outstanding Graduates, a testament to my dedication to scholarly pursuits.
🚀 Professional Endeavors: Bridging Academia and Industry
To broaden my exposure to global research and industry practices, I took on the role of Project Assistant at the Hong Kong Polytechnic University in the Department of Logistics and Shipping Management. My brief tenure from June to October 2022 provided invaluable insights into logistics optimization and project execution. Additionally, my academic journey was enriched through my participation in a joint training program at Eindhoven University of Technology, where I delved into Industrial Engineering and Innovation under the prestigious CSC program. This cross-border research experience has been instrumental in shaping my analytical approach and problem-solving skills.
📚 Contributions and Research Focus: Advancing Logistics and Optimization
My research primarily focuses on operational optimization, deep reinforcement learning, and robust decision-making models in logistics and transportation. I have had the privilege of publishing multiple high-impact papers in SCI-indexed journals, with notable contributions including:
- The application of deep reinforcement learning for UAV-based rolling horizon team orienteering problems in maritime logistics.
- Multi-stage humanitarian emergency logistics decision-making under uncertainty, published in Natural Hazards.
- The integration of motherships and UAVs for ship emission inspection, enhancing environmental compliance in maritime operations.
- Robust optimization approaches applied to cold chain logistics, inventory routing, and emergency response planning. These works contribute significantly to the optimization of logistics systems, particularly in high-risk and dynamic environments.
🏆 Accolades and Recognition: Celebrating Achievements
My dedication to research and innovation has been recognized on multiple platforms. In June 2023, I presented at the 13th Annual Global Chinese Industrial Engineering Conference, where I was honored with the Excellent Paper Award for my work on MaaS-based fleet size and scheduling of demand-responsive subway shuttle EVs. Such accolades serve as motivation to continue pushing the boundaries of logistics optimization.
📈 Impact and Influence: Shaping Future Innovations
Beyond publications and awards, my work has practical implications for industries seeking to enhance operational efficiency, reduce environmental impact, and optimize emergency response strategies. My research in robust optimization and deep learning models has been instrumental in proposing more resilient and adaptive logistics frameworks, particularly for humanitarian and maritime applications. These contributions pave the way for smarter, more sustainable logistics solutions in an era of rapid technological advancements.
🌟 Legacy and Future Contributions: A Vision for Excellence
As I complete my Ph.D. at Sichuan University in Management Science and Engineering, I remain committed to contributing to the field through collaborative research, mentorship, and innovative problem-solving. My aspiration is to continue developing intelligent logistics systems, leveraging AI-driven methodologies to tackle pressing challenges in transportation, supply chain management, and emergency response planning. The future holds endless possibilities, and I am eager to be at the forefront of transformative advancements in logistics engineering.
Publication
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Ship emission inspection with a joint mode of motherships and unmanned aerial vehicles
Authors: Jianhui Du, Dan Zhuge, Lu Zhen, Shuaian Wang, Peng Wu
Year: 2025
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Research progress and perspectives on carbon capture, utilization, and storage (CCUS) technologies in China and the USA: a bibliometric analysis
Authors: Qiang Ren, Shansen Wei, Jianhui Du, Peng Wu
Year: 2023
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Multi-stage humanitarian emergency logistics: robust decisions in uncertain environment
Authors: Jianhui Du, Peng Wu, Yiqing Wang, Dan Yang
Year: 2023
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Two-stage mean-risk stochastic mixed integer optimization model for location-allocation problems under uncertain environment
Authors: Zhimin Liu, Shaojian Qu, Hassan Raza, Zhong Wu, Deqiang Qu, Jianhui Du
Year: 2021
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Robust optimization approach to two-echelon agricultural cold chain logistics considering carbon emission and stochastic demand
Authors: Ying Ji, Jianhui Du, Xiaoqing Wu, Zhong Wu, Deqiang Qu, Dan Yang
Year: 2021
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Three-Stage Mixed Integer Robust Optimization Model Applied to Humanitarian Emergency Logistics by Considering Secondary Disasters
Authors: Jianhui Du, Ying Ji, Deqiang Qu, Wu Xiaoqing, Dan Yang
Year: 2020
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A mixed integer robust programming model for two-echelon inventory routing problem of perishable products
Authors: Ying Ji, Jianhui Du, Xiaoya Han, Xiaoqing Wu, Ripeng Huang, Shilei Wang, Zhimin Liu
Year: 2020
Conclusion
This academic journey has been both challenging and fulfilling, driven by my unwavering passion for research and problem-solving. I am grateful for the opportunities that have shaped my expertise and the mentors who have guided me along the way. With a solid foundation in logistics engineering, deep reinforcement learning, and operational optimization, I look forward to making further contributions that leave a lasting impact on academia and industry alike.