Cargando…
Memory-based variable neighborhood search for green vehicle routing problem with passing-by drivers: a comprehensive perspective
A business delivery model with professional vehicles as well as occasional passing-by vehicles is investigated in this paper. The drivers deliver parcels from the distribution center to customers and the passing-by driver can get a certain amount of compensation in return. To give a satisfactory sol...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8824391/ https://www.ncbi.nlm.nih.gov/pubmed/35155081 http://dx.doi.org/10.1007/s40747-022-00661-5 |
_version_ | 1784647006564646912 |
---|---|
author | Cao, Lei Ye, Chun-ming Cheng, Ran Wang, Zhen-kun |
author_facet | Cao, Lei Ye, Chun-ming Cheng, Ran Wang, Zhen-kun |
author_sort | Cao, Lei |
collection | PubMed |
description | A business delivery model with professional vehicles as well as occasional passing-by vehicles is investigated in this paper. The drivers deliver parcels from the distribution center to customers and the passing-by driver can get a certain amount of compensation in return. To give a satisfactory solution from the perspective of platform owner, customers, professional drivers, occasional drivers, and authority, a multi-layer comprehensive model is proposed. To effectively solve the proposed model, we introduce an improved variable neighborhood search (VNS) with a memory-based restart mechanism. The new algorithm is evaluated on instances derived from Solomon’s benchmark and real-life beer delivery instances. Taguchi experiment is used to tune parameters in the proposed VNS, followed by component analysis and real-life experiments. Experimental results indicate that the proposed strategies are effective and the new delivery model in this paper has some advantages over traditional and single-delivery ones from the comprehensive perspectives of stakeholders in the crowdsourcing logistics system. |
format | Online Article Text |
id | pubmed-8824391 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-88243912022-02-09 Memory-based variable neighborhood search for green vehicle routing problem with passing-by drivers: a comprehensive perspective Cao, Lei Ye, Chun-ming Cheng, Ran Wang, Zhen-kun Complex Intell Systems Original Article A business delivery model with professional vehicles as well as occasional passing-by vehicles is investigated in this paper. The drivers deliver parcels from the distribution center to customers and the passing-by driver can get a certain amount of compensation in return. To give a satisfactory solution from the perspective of platform owner, customers, professional drivers, occasional drivers, and authority, a multi-layer comprehensive model is proposed. To effectively solve the proposed model, we introduce an improved variable neighborhood search (VNS) with a memory-based restart mechanism. The new algorithm is evaluated on instances derived from Solomon’s benchmark and real-life beer delivery instances. Taguchi experiment is used to tune parameters in the proposed VNS, followed by component analysis and real-life experiments. Experimental results indicate that the proposed strategies are effective and the new delivery model in this paper has some advantages over traditional and single-delivery ones from the comprehensive perspectives of stakeholders in the crowdsourcing logistics system. Springer International Publishing 2022-02-08 2022 /pmc/articles/PMC8824391/ /pubmed/35155081 http://dx.doi.org/10.1007/s40747-022-00661-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Cao, Lei Ye, Chun-ming Cheng, Ran Wang, Zhen-kun Memory-based variable neighborhood search for green vehicle routing problem with passing-by drivers: a comprehensive perspective |
title | Memory-based variable neighborhood search for green vehicle routing problem with passing-by drivers: a comprehensive perspective |
title_full | Memory-based variable neighborhood search for green vehicle routing problem with passing-by drivers: a comprehensive perspective |
title_fullStr | Memory-based variable neighborhood search for green vehicle routing problem with passing-by drivers: a comprehensive perspective |
title_full_unstemmed | Memory-based variable neighborhood search for green vehicle routing problem with passing-by drivers: a comprehensive perspective |
title_short | Memory-based variable neighborhood search for green vehicle routing problem with passing-by drivers: a comprehensive perspective |
title_sort | memory-based variable neighborhood search for green vehicle routing problem with passing-by drivers: a comprehensive perspective |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8824391/ https://www.ncbi.nlm.nih.gov/pubmed/35155081 http://dx.doi.org/10.1007/s40747-022-00661-5 |
work_keys_str_mv | AT caolei memorybasedvariableneighborhoodsearchforgreenvehicleroutingproblemwithpassingbydriversacomprehensiveperspective AT yechunming memorybasedvariableneighborhoodsearchforgreenvehicleroutingproblemwithpassingbydriversacomprehensiveperspective AT chengran memorybasedvariableneighborhoodsearchforgreenvehicleroutingproblemwithpassingbydriversacomprehensiveperspective AT wangzhenkun memorybasedvariableneighborhoodsearchforgreenvehicleroutingproblemwithpassingbydriversacomprehensiveperspective |