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Dynamic On-Demand Crowdshipping Using Heuristics-Embedded and Constrained Deep Reinforcement Learning

Research Seminar Series

20221005Prof Bo ZouEvent Banner
  • Date

    05 Oct 2022

  • Organiser

    Department of Industrial and Systems Engineering, PolyU; Research Institute for Advanced Manufacturing (RIAM)

  • Time

    09:30 - 11:00

  • Venue

    Online via ZOOM  

Speaker

Prof. Bo Zou

Remarks

Meeting link will be sent to successful registrants

20221005Prof Bo ZouPoster

Summary

Crowdsourced parcel delivery, or crowdshipping, has emerged recently as a crucial component of city logistics and an attractive alternative to conventional van/truck-based delivery. By employing ordinary people (termed crowdsources) who use spare time to perform pickup and delivery by walking, biking, or driving personal cars as opposed to using company-owned vans or trucks, crowdshipping helps reduce shipping cost and freight traffic-related congestion, parking demand, energy use, and emissions, all of which contribute to more sustainable urban communities. In this talk, I will present my group’s recent research in heuristics-embedded and constrained deep reinforcement learning (DRL) to tackle the key problem of crowdsource-shipping request assignment in a dynamic on-demand crowdshipping environment. The idea of heuristics-embedded training is conceived by designing an elaborate action space where refined local search heuristics are conceived and embedded to direct the specific action to take once an action type is chosen by DRL, to preserve tractability of DRL training. To tackle the hard constraints pertaining to crowdsource and shipping request time windows, we propose and integrate three new strategies (feasibility enforced local search, multiple schedules with different penalties, and exponential penalty) as part of the DRL training and testing. Extensive numerical analysis on adopting the proposed approach with multiple DRL algorithms is performed. By comparing the proposed approach with conventional heuristic methods, benchmarking the results against global optimality, and testing result sensitivity to demand pattern variations, weD demonstrate superior performance of the approach in solution quality, computational efficiency, and robustness, and thus potential for practical implementation.

Keynote Speaker

Prof. Bo Zou

Prof. Bo Zou

Associate Professor
Department of Civil, Materials, and Environmental Engineering,
University of Illinois Chicago, 
United States

Prof. Bo Zou is an associate professor in the Department of Civil, Materials, and Environmental Engineering at the University of Illinois Chicago. He is also a visiting associate professor in the Department of Civil and Environmental Engineering at the University of California, Berkeley. Prof. Zou received his Ph.D. in transportation engineering with minors in industrial engineering and operations research, and economics (UC Berkeley), M.S. in transportation planning and management (Tsinghua University, China), Diplôme d’Ingénieur in general engineering (Ecole Centrale Nantes, France), and B.E. in civil engineering (Tsinghua University, China). Prof. Zou’s recent research interest has been on technology innovations that are happening and reshaping human and freight mobility. In pursuing the uncharted areas, his research has received funding support from agencies including the World Bank, the US National Science Foundation, NASA, the US Department of Transportation, the US Department of Energy, the American Public Transportation Association, and state and city government agencies. Prof. Zou serves a number of roles in the transportation research community, including as an associate editor of Transportation Letters, an editorial board editor of Transportation Research Part B: Methodological, an editorial board member of both Transportation Research Part C: Emerging Technologies and Transportation Research Parts E: Logistics and Transportation Review, and editorial board lead of the Freight Transportation Planning and Logistics (AT015) Committee of the Transportation Research Board of the National Academies.  

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