The low-carbon vehicle routing problem with dynamic speed on steep roads
The low-carbon vehicle routing problem with dynamic speeds on steep roads (LCVRPDS-SR) considers the combined effects of dynamic speeds, steep roads, and loads on carbon emissions. Earlier low-carbon vehicle routing problems typically assumed that vehicles travel at a constant speed on flat roads. H...
Saved in:
Main Authors: | , , , , , |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2024
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/9338 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
id |
sg-smu-ink.sis_research-10338 |
---|---|
record_format |
dspace |
spelling |
sg-smu-ink.sis_research-103382024-09-26T07:06:03Z The low-carbon vehicle routing problem with dynamic speed on steep roads XIAO, Jianhua LIU, Xiaoyang ZHANG, Huixian CAO, Zhiguang KANG, Liujiang NIU, Yunyun The low-carbon vehicle routing problem with dynamic speeds on steep roads (LCVRPDS-SR) considers the combined effects of dynamic speeds, steep roads, and loads on carbon emissions. Earlier low-carbon vehicle routing problems typically assumed that vehicles travel at a constant speed on flat roads. However, such models do not apply in urban or rural areas with steep roads. Although the subsequent studies further explored the effect of steep roads, their performance are still suboptimal since they fail to take into account the varying speeds on the terrain. This paper proposes an extended LCVRPDS-SR model that tackles dynamic speed decisions on steep roads for the low-carbon vehicle routing problem. The objective function is non-linear and considers only environmental factors. Then an improved adaptive large neighborhood search algorithm is presented, including a new speed optimization algorithm and several improved removal and insertion operators. Extensive experiments are conducted on the generated instances to verify the effectiveness of the model and algorithm and derive managerial insights. The significant reduction in greenhouse gas emissions is achieved when considering dynamic speeds. 2024-06-17T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/9338 info:doi/10.1016/j.cor.2024.106736 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Low-carbon vehicle routing problem Steep roads Dynamic speed decision Adaptive large neighborhood algorithm Artificial Intelligence and Robotics Theory and Algorithms |
institution |
Singapore Management University |
building |
SMU Libraries |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
SMU Libraries |
collection |
InK@SMU |
language |
English |
topic |
Low-carbon vehicle routing problem Steep roads Dynamic speed decision Adaptive large neighborhood algorithm Artificial Intelligence and Robotics Theory and Algorithms |
spellingShingle |
Low-carbon vehicle routing problem Steep roads Dynamic speed decision Adaptive large neighborhood algorithm Artificial Intelligence and Robotics Theory and Algorithms XIAO, Jianhua LIU, Xiaoyang ZHANG, Huixian CAO, Zhiguang KANG, Liujiang NIU, Yunyun The low-carbon vehicle routing problem with dynamic speed on steep roads |
description |
The low-carbon vehicle routing problem with dynamic speeds on steep roads (LCVRPDS-SR) considers the combined effects of dynamic speeds, steep roads, and loads on carbon emissions. Earlier low-carbon vehicle routing problems typically assumed that vehicles travel at a constant speed on flat roads. However, such models do not apply in urban or rural areas with steep roads. Although the subsequent studies further explored the effect of steep roads, their performance are still suboptimal since they fail to take into account the varying speeds on the terrain. This paper proposes an extended LCVRPDS-SR model that tackles dynamic speed decisions on steep roads for the low-carbon vehicle routing problem. The objective function is non-linear and considers only environmental factors. Then an improved adaptive large neighborhood search algorithm is presented, including a new speed optimization algorithm and several improved removal and insertion operators. Extensive experiments are conducted on the generated instances to verify the effectiveness of the model and algorithm and derive managerial insights. The significant reduction in greenhouse gas emissions is achieved when considering dynamic speeds. |
format |
text |
author |
XIAO, Jianhua LIU, Xiaoyang ZHANG, Huixian CAO, Zhiguang KANG, Liujiang NIU, Yunyun |
author_facet |
XIAO, Jianhua LIU, Xiaoyang ZHANG, Huixian CAO, Zhiguang KANG, Liujiang NIU, Yunyun |
author_sort |
XIAO, Jianhua |
title |
The low-carbon vehicle routing problem with dynamic speed on steep roads |
title_short |
The low-carbon vehicle routing problem with dynamic speed on steep roads |
title_full |
The low-carbon vehicle routing problem with dynamic speed on steep roads |
title_fullStr |
The low-carbon vehicle routing problem with dynamic speed on steep roads |
title_full_unstemmed |
The low-carbon vehicle routing problem with dynamic speed on steep roads |
title_sort |
low-carbon vehicle routing problem with dynamic speed on steep roads |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2024 |
url |
https://ink.library.smu.edu.sg/sis_research/9338 |
_version_ |
1814047913949528064 |