The Optimization Model and Application of Crowdsourcing Logistics Distribution Considering the Travel Trajectory of Deliverers

DOI

10.2991/978-94-6463-570-6_109How to use a DOI?

Keywords

crowdsourcing delivery; supply and demand matching; path planning; genetic algorithms

Abstract

The problems of supply and demand matching and route planning of crowdsourcing platform are the development difficulties faced by urban distribution O2O platform. This paper stands on the Angle of the platform, considers the actual needs of crowdsourcing distributors and customers at the same time, and introduces the general idea of single-place booking processing time window. Taking into account the customer’s expected delivery time window, credibility requirements, the deviation distance limit of crowdsourcing deliverers, the start and end point, the distribution capacity limit system and other factors, without considering the refusal of orders, A multi-objective optimization model is constructed to minimize the total distribution cost, maximize customer satisfaction and minimize the deviation distance of crowdsourcing deliverers. Finally, according to the characteristics of the model, greedy algorithm and genetic algorithm are used to solve it, and the case data of a unit in a city and a district of SF Company is selected for empirical analysis. The results of the study show that the quality of the method is significantly higher than that of the greedy method, the optimization ratio reaches 8.5%, and the benefits of crowdsourcing deliverers, customers and crowdsourcing platforms are maximized.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Qiang Wu
AU  - Jun Tu
PY  - 2024
DA  - 2024/11/22
TI  - The Optimization Model and Application of Crowdsourcing Logistics Distribution Considering the Travel Trajectory of Deliverers
BT  - Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024)
PB  - Atlantis Press
SP  - 1089
EP  - 1097
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-570-6_109
DO  - 10.2991/978-94-6463-570-6_109
ID  - Wu2024
ER  -