Route Design for Freight Trip Based on an Enhanced Greedy Algorithm
- DOI
- 10.2991/978-2-494069-45-9_15How to use a DOI?
- Keywords
- Greedy algorithm; Route design; Freight
- Abstract
As a result of the COVID-19 pandemic, online shopping, due to its convenience and ever-improving digital experience, is rapidly becoming the preferred method of purchasing for by an increasing number of individuals. With the efficiency of purchasing improving, the growing number of orders puts more pressure on freight. Consequently, the deliverymen must deliver more packages than they did before and face a substantial rise in their workload. Arguably, it is crucial to re-construct and optimize the delivery routes to reduce the workload of the delivery staff, increase customer satisfaction, and lower the company’s expenses. This research aims present an enhanced greedy algorithm for designing more efficient delivery routes to reduce delivery distance and delivery time. The author generates several edges to simulate city-to-city routes and utilize C++ software as a tool to apply an enhanced greedy algorithm to determine the optimal path for delivery. It can be concluded from the experiment that the paths built with the enhanced greedy algorithm provide optimal results compared to those generated with the greedy algorithm that is not restricted by factors like time and number of packages. The end results of lowering the delivery time of packages and decreasing the distance of delivering can demonstrate the effectiveness of the enhanced greedy algorithm in express delivery path planning.
- Copyright
- © 2023 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.
Cite this article
TY - CONF AU - Mingjun Yan PY - 2022 DA - 2022/12/16 TI - Route Design for Freight Trip Based on an Enhanced Greedy Algorithm BT - Proceedings of the 2022 2nd International Conference on Modern Educational Technology and Social Sciences (ICMETSS 2022) PB - Atlantis Press SP - 115 EP - 120 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-494069-45-9_15 DO - 10.2991/978-2-494069-45-9_15 ID - Yan2022 ER -