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JACIII Vol.26 No.2 pp. 147-159
doi: 10.20965/jaciii.2022.p0147
(2022)

Paper:

Research on Delivery Network Optimization Based on Crowdsourcing Theory

Jiacheng Li*, Masato Noto*, and Yang Zhang**

*Department of Electrical, Electronics and Information Engineering, Kanagawa University
3-27-1 Rokkakubashi, Kanagawa-ku, Yokohama, Kanagawa 221-8686, Japan

**Graduate School of Science and Engineering, Hosei University
3-7-2 Kajino-cho, Koganei, Tokyo 184-8584, Japan

Received:
May 20, 2021
Accepted:
December 27, 2021
Published:
March 20, 2022
Keywords:
takeaway fast food, crowdsourcing distribution, order allocation, path optimization
Abstract
Research on Delivery Network Optimization Based on Crowdsourcing Theory

Distribution routes of crowdsourcing workers (a)-(j)

Under a new wave of technological revolution and industrial change, Internet plus has penetrated into every aspect of production and life. For the traditional takeout industry, the new crowdsourcing distribution mode based on o2o (online to offline) provides new ideas for distribution but also leads to great challenges. In view of the existing development problems and transformation needs of the delivery network, this paper explores the delivery mechanism of delivery orders in crowdsourcing mode, focusing on the delivery path and work efficiency. To optimize the delivery network, taking the shortest delivery path and the least time delay as objectives, this paper establishes a crowdsourcing delivery path optimization model with a time window and includes an example application model. The results show that the model can solve the delivery problem in crowdsourcing mode.

Cite this article as:
Jiacheng Li, Masato Noto, and Yang Zhang, “Research on Delivery Network Optimization Based on Crowdsourcing Theory,” J. Adv. Comput. Intell. Intell. Inform., Vol.26, No.2, pp. 147-159, 2022.
Data files:
References
  1. [1] Y. Chen, “Location and Pricing of Terminal Distribution Based on Customer Choice Equilibrium,” Doctral Thesis, Southwest Jiaotong University, 2018 (in Chinese).
  2. [2] Y. Ding, “Study on Delivery Mode Selection of MeiTuan Takeout,” Master Thesis, Nanjing University, 2015 (in Chinese).
  3. [3] J. Howe, “The Rise of Crowd Sourcing,” Wired, Vol.149, No.6, pp. 176-183, 2006.
  4. [4] D. K. Tse and P. C. Wilton, “Models of Consumer Satisfaction Formation: An Extension,” J. of Marketing Research, Vol.25, No.2, pp. 204-212, 1988.
  5. [5] O. Toubia, “Idea Generation, Creativity, and Incentives,” Marketing Science, Vol.25, No.5, pp. 411-425, 2006.
  6. [6] H. Yong, “Crowdsourcing: Amateur Bedizens Beat Corporate Superman,” CEIBS Business Review, No.3, pp. 38-46, 2009.
  7. [7] N. Thrift, “Re-inventing Invention: New Tendencies in Capitalist Commodification,” Economy and Society, Vol.35, No.2, pp. 279-306, 2006.
  8. [8] Wikipedia, “Crowdsourcing,” https://en.wikipedia.org/wiki/Crowdsourcing [accessed October 30, 2021]
  9. [9] D. C. Brabham, “Crowdsourcing as a Model for Problem Solving: An Introduction and Cases,” The Int. J. of Research into New Media Technologies, Vol.14, No.1, pp. 75-90, 2008.
  10. [10] M. Wang, “Optimization of Logistics Distribution Scheduling Based on Crowdsourcing,” Master Thesis, Harbin Institute of Technology, 2017 (in Chinese).
  11. [11] G. Berbeglia, J.-F. Cordeau, and G. Laporte, “Dynamic Pickup and Delivery Problems,” European J. of Operational Research, Vol.202, No.1, pp. 8-15, 2010.
  12. [12] G. Berbeglia, J.-F. Cordeau, I. Gribkovskaia et al., “Static Pickup and Delivery Problems: A Classification Scheme and Survey,” Top, Vol.15, No.1, pp. 1-31, 2007.
  13. [13] M. A. Klapp, A. L. Erera, and A. Toriello, “The One-dimensional Dynamic Dispatch Waves Problem,” Transportation Science, Vol.52, No.2, pp. 229-496, 2018.
  14. [14] S. A. Voccia, A. M. Campbell, and B. W. Thomas, “The Same-day Delivery Problem for Online Purchases,” Transportation Science, Vol.53, No.1, pp. 1-318, 2019.
  15. [15] A. M. Arslan, N. A. H. Agatz, L. G. Kroon et al., “Crowdsourced Delivery: A Dynamic Pickup and Delivery Problem with Ad-hoc Drivers,” ERIM Report Series Research in Management, No.ERS-2016-003-LIS, 2016.
  16. [16] M. Bortolini, M. Faccio, E. Ferrari et al., “Fresh Food Sustainable Distribution: Cost, Delivery Time and Carbon Footprint Three-objective Optimization,” J. of Food Engineering, Vol.174, No.85, pp. 56-67, 2016.
  17. [17] H. I. Calvete, C. Galé, and J. A. Iranzo, “Planning of a Decentralized Distribution Network Using Bilevel Optimization,” Omega, Vol.49, No.12, pp. 30-41, 2014.
  18. [18] Y. Wang, X. Ma, M. Xu et al., “Two-echelon Logistics Distribution Region Partitioning Problem Based on a Hybrid Particle Swarm Optimization-Genetic Algorithm,” Expert Systems with Applications, Vol.42, No.12, pp. 5019-5031, 2015.
  19. [19] J. Li and L. Li, “A Study on the Takeaway Distribution Network Based on the Crowd Sourcing Theory,” Proc. of the 9th Int. Conf. on Information, Tokyo, Japan, No.25, pp. 87-96, 2018.
  20. [20] B. Shen, Y. Zhao, Y. Huang et al., “Survey on Dynamic Ride Sharing in Big Data Era,” J. of Computer Research and Development, Vol.54, No.1, pp. 34-49, 2017 (in Chinese and English abstract).
  21. [21] X. Du, “Research on Matching Path Optimization Under One to Many Situations in Private Car Sharing,” Master Thesis, Chang’an University, 2017 (in Chinese).
  22. [22] T. Chunjin, “Research on the Piggybacking Method of the Multi-cluster and Scattered Vehicle Routing Problem,” Chongqing University, 2010 (in Chinese).
  23. [23] J. Xu, “Research on Vehicle Route Planning Problem with Time Window and Delivery and Pickup,” Master Thesis, Jinan University, 2018 (in Chinese).
  24. [24] F. Zhao, “Dynamic Path Planning Based on Ant Colony Algorithm and Its Simulation Application in Formation,” Master Thesis, Kunming University of Science and Technology, 2017 (in Chinese).
  25. [25] Z. Tu, “Research on Dynamic Path Planning Based on Evolution and Reinforcement Learning Algorithms,” Master Thesis, University of Electronic Science and Technology, 2020 (in Chinese).
  26. [26] Y. Sui, “The Research on Dynamic Path Planning Algorithms and Navigation Software Design,” Master Thesis, University of Science and Technology of China, 2015 (in Chinese).
  27. [27] S. Cheng, “Research and Implementation of Dynamic Road Network Path Planning Algorithm Under Time Limitation,” Master Thesis, University of Science and Technology of China, 2015 (in Chinese).
  28. [28] Z. Wang, “Research on Distribution and Route Optimization of Takeaway Orders Under Crowdsourcing Delivery Mode,” Master Thesis, Donghua University, 2020 (in Chinese).
  29. [29] C. Yong, “Research on Integrated Delivery Vehicle Path Planning in Crowdsourcing Mode,” Hefei University of Technology, 2020 (in Chinese).
  30. [30] X. Chen, “Research on the Optimization of the End Distribution Route of Express Companies under the Crowdsourcing Mode,” Master Thesis, Zhejiang Gongshang University, 2018 (in Chinese).
  31. [31] R. Tong, “Study on Optimization of Takeout Delivery Path Based on Crowdsourcing Model,” Master Thesis, Xi’an University of Technology, 2019 (in Chinese).

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Last updated on May. 20, 2022