An improved ant colony optimization algorithm based on context for tourism route planning.

To solve the problem of one-sided pursuit of the shortest distance but ignoring the tourist experience in the process of tourism route planning, an improved ant colony optimization algorithm is proposed for tourism route planning. Contextual information of scenic spots significantly effect people�...

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Autores principales:	Shengbin Liang, Tongtong Jiao, Wencai Du, Shenming Qu
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/0c624077c9fc46c783937fcb63be084f
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spelling	oai:doaj.org-article:0c624077c9fc46c783937fcb63be084f2021-12-02T20:06:14ZAn improved ant colony optimization algorithm based on context for tourism route planning.1932-620310.1371/journal.pone.0257317https://doaj.org/article/0c624077c9fc46c783937fcb63be084f2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0257317https://doaj.org/toc/1932-6203To solve the problem of one-sided pursuit of the shortest distance but ignoring the tourist experience in the process of tourism route planning, an improved ant colony optimization algorithm is proposed for tourism route planning. Contextual information of scenic spots significantly effect people's choice of tourism destination, so the pheromone update strategy is combined with the contextual information such as weather and comfort degree of the scenic spot in the process of searching the global optimal route, so that the pheromone update tends to the path suitable for tourists. At the same time, in order to avoid falling into local optimization, the sub-path support degree is introduced. The experimental results show that the optimized tourism route has greatly improved the tourist experience, the route distance is shortened by 20.5% and the convergence speed is increased by 21.2% compared with the basic algorithm, which proves that the improved algorithm is notably effective.Shengbin LiangTongtong JiaoWencai DuShenming QuPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 9, p e0257317 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Shengbin Liang Tongtong Jiao Wencai Du Shenming Qu An improved ant colony optimization algorithm based on context for tourism route planning.
description	To solve the problem of one-sided pursuit of the shortest distance but ignoring the tourist experience in the process of tourism route planning, an improved ant colony optimization algorithm is proposed for tourism route planning. Contextual information of scenic spots significantly effect people's choice of tourism destination, so the pheromone update strategy is combined with the contextual information such as weather and comfort degree of the scenic spot in the process of searching the global optimal route, so that the pheromone update tends to the path suitable for tourists. At the same time, in order to avoid falling into local optimization, the sub-path support degree is introduced. The experimental results show that the optimized tourism route has greatly improved the tourist experience, the route distance is shortened by 20.5% and the convergence speed is increased by 21.2% compared with the basic algorithm, which proves that the improved algorithm is notably effective.
format	article
author	Shengbin Liang Tongtong Jiao Wencai Du Shenming Qu
author_facet	Shengbin Liang Tongtong Jiao Wencai Du Shenming Qu
author_sort	Shengbin Liang
title	An improved ant colony optimization algorithm based on context for tourism route planning.
title_short	An improved ant colony optimization algorithm based on context for tourism route planning.
title_full	An improved ant colony optimization algorithm based on context for tourism route planning.
title_fullStr	An improved ant colony optimization algorithm based on context for tourism route planning.
title_full_unstemmed	An improved ant colony optimization algorithm based on context for tourism route planning.
title_sort	improved ant colony optimization algorithm based on context for tourism route planning.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/0c624077c9fc46c783937fcb63be084f
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An improved ant colony optimization algorithm based on context for tourism route planning.

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