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.

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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  -