A Novel Multi-Objective and Multi-Constraint Route Recommendation Method Based on Crowd Sensing

Nowadays, people choose to travel in their leisure time more frequently, but fixed predetermined tour routes can barely meet people’s personalized preferences. The needs of tourists are diverse, largely personal, and possibly have multiple constraints. The traditional single-objective route planning...

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Autores principales:	Xiaoyao Zheng, Yonglong Luo, Liping Sun, Qingying Yu, Ji Zhang, Siguang Chen
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	crowd sensing multi-constraint route recommendation multi-objective Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/40300596a72b4fac99245c85b8cd207f
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spelling	oai:doaj.org-article:40300596a72b4fac99245c85b8cd207f2021-11-11T15:25:56ZA Novel Multi-Objective and Multi-Constraint Route Recommendation Method Based on Crowd Sensing10.3390/app1121104972076-3417https://doaj.org/article/40300596a72b4fac99245c85b8cd207f2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10497https://doaj.org/toc/2076-3417Nowadays, people choose to travel in their leisure time more frequently, but fixed predetermined tour routes can barely meet people’s personalized preferences. The needs of tourists are diverse, largely personal, and possibly have multiple constraints. The traditional single-objective route planning algorithm struggles to effectively deal with such problems. In this paper, a novel multi-objective and multi-constraint tour route recommendation method is proposed. Firstly, ArcMap was used to model the actual road network. Then, we created a new interest label matching method and a utility function scoring method based on crowd sensing, and constructed a personalized multi-constraint interest model. We present a variable neighborhood search algorithm and a hybrid particle swarm genetic optimization algorithm for recommending Top-K routes. Finally, we conducted extensive experiments on public datasets. Compared with the ATP route recommendation method based on an improved ant colony algorithm, our proposed method is superior in route score, interest abundance, number of POIs, and running time.Xiaoyao ZhengYonglong LuoLiping SunQingying YuJi ZhangSiguang ChenMDPI AGarticlecrowd sensingmulti-constraintroute recommendationmulti-objectiveTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10497, p 10497 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	crowd sensing multi-constraint route recommendation multi-objective Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	crowd sensing multi-constraint route recommendation multi-objective Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Xiaoyao Zheng Yonglong Luo Liping Sun Qingying Yu Ji Zhang Siguang Chen A Novel Multi-Objective and Multi-Constraint Route Recommendation Method Based on Crowd Sensing
description	Nowadays, people choose to travel in their leisure time more frequently, but fixed predetermined tour routes can barely meet people’s personalized preferences. The needs of tourists are diverse, largely personal, and possibly have multiple constraints. The traditional single-objective route planning algorithm struggles to effectively deal with such problems. In this paper, a novel multi-objective and multi-constraint tour route recommendation method is proposed. Firstly, ArcMap was used to model the actual road network. Then, we created a new interest label matching method and a utility function scoring method based on crowd sensing, and constructed a personalized multi-constraint interest model. We present a variable neighborhood search algorithm and a hybrid particle swarm genetic optimization algorithm for recommending Top-K routes. Finally, we conducted extensive experiments on public datasets. Compared with the ATP route recommendation method based on an improved ant colony algorithm, our proposed method is superior in route score, interest abundance, number of POIs, and running time.
format	article
author	Xiaoyao Zheng Yonglong Luo Liping Sun Qingying Yu Ji Zhang Siguang Chen
author_facet	Xiaoyao Zheng Yonglong Luo Liping Sun Qingying Yu Ji Zhang Siguang Chen
author_sort	Xiaoyao Zheng
title	A Novel Multi-Objective and Multi-Constraint Route Recommendation Method Based on Crowd Sensing
title_short	A Novel Multi-Objective and Multi-Constraint Route Recommendation Method Based on Crowd Sensing
title_full	A Novel Multi-Objective and Multi-Constraint Route Recommendation Method Based on Crowd Sensing
title_fullStr	A Novel Multi-Objective and Multi-Constraint Route Recommendation Method Based on Crowd Sensing
title_full_unstemmed	A Novel Multi-Objective and Multi-Constraint Route Recommendation Method Based on Crowd Sensing
title_sort	novel multi-objective and multi-constraint route recommendation method based on crowd sensing
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/40300596a72b4fac99245c85b8cd207f
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A Novel Multi-Objective and Multi-Constraint Route Recommendation Method Based on Crowd Sensing

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