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Interactive planning of revisiting-free itinerary for signed-for delivery

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Abstract

The trend of online shopping has given rise to the growth of signed-for delivery services. Signed-for delivery is a reliable way of getting proof of delivery that ensures your parcel must be signed for upon its arrival with the recipient. However, due to the unknown of recipient occupancy, general signed-for delivery is not very effective for delivery drivers. Once the recipients are not available upon drivers’ arrival, drivers have to arrange revisiting the recipients, causing the resource waste and being overworked. In this paper, we address an important issue on the revisiting-free itinerary planning and propose a novel interactive planning system, called COKI, to interactively plan the effective delivery itineraries with a round-by-round strategy. The flow enables delivery drivers to take a shorter itinerary without revisiting any recipient. Our experimental studies on real data show that, without properly considering the issues in revisiting-free paradigm, the extension of state-of-the-art routing algorithms can only achieve sub-optimal results. Furthermore, the COKI framework can efficiently discover better revisiting-free itinerary for signed-for delivery in an interactive fashion.

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Notes

  1. Please refer to http://rossa-prod-ap11.ethz.ch/delivery/DeliveryManagerServlet?dps_pid=IE594964 for the electricity consumption data.

  2. Please refer to https://figshare.com/articles/Urban_Road_Network_Data/2061897 for the urban road network data.

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Acknowledgements

This work was supported in part by Ministry of Science and Technology, R.O.C., under Contract 109-2221-E-006-187-MY3, 110-2221-E-006-001 and 111AT16B.

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Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan City, Taiwan

    Lo Pang-Yun Ting, Shan-Yun Teng, Szu-Chan Wu & Kun-Ta Chuang

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Ting, L.PY., Teng, SY., Wu, SC. et al. Interactive planning of revisiting-free itinerary for signed-for delivery. Int J Data Sci Anal 14, 439–456 (2022). https://doi.org/10.1007/s41060-022-00333-0

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