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Particle Swarm Algorithm and Its Application in Tourism Route Design and Optimization
Most of the traditional tourism route planning algorithms only consider single-factor planning, that is, the influence of scenic spots on route planning. Particle swarm optimization algorithm is favored by many people because of its simple concept, easy implementation, and good robustness. Aiming at...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8983212/ https://www.ncbi.nlm.nih.gov/pubmed/35392048 http://dx.doi.org/10.1155/2022/6467086 |
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author | Lu, Bing Zhou, Chunlei |
author_facet | Lu, Bing Zhou, Chunlei |
author_sort | Lu, Bing |
collection | PubMed |
description | Most of the traditional tourism route planning algorithms only consider single-factor planning, that is, the influence of scenic spots on route planning. Particle swarm optimization algorithm is favored by many people because of its simple concept, easy implementation, and good robustness. Aiming at this problem, this paper takes the actual geographic data as the research object of the tourism route problem and describes the model of the discrete particle swarm algorithm based on geographic coordinates to solve the tourism route problem, which is used to solve practical problems. In order to further improve the global search ability of the algorithm, a self-balancing mechanism is proposed, which makes the algorithm process simple and the algorithm performance improved. At the same time, multithread parallelism is adopted to improve the solution speed of the algorithm, which makes up for the deficiency of the parallelization research of the algorithm. |
format | Online Article Text |
id | pubmed-8983212 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-89832122022-04-06 Particle Swarm Algorithm and Its Application in Tourism Route Design and Optimization Lu, Bing Zhou, Chunlei Comput Intell Neurosci Research Article Most of the traditional tourism route planning algorithms only consider single-factor planning, that is, the influence of scenic spots on route planning. Particle swarm optimization algorithm is favored by many people because of its simple concept, easy implementation, and good robustness. Aiming at this problem, this paper takes the actual geographic data as the research object of the tourism route problem and describes the model of the discrete particle swarm algorithm based on geographic coordinates to solve the tourism route problem, which is used to solve practical problems. In order to further improve the global search ability of the algorithm, a self-balancing mechanism is proposed, which makes the algorithm process simple and the algorithm performance improved. At the same time, multithread parallelism is adopted to improve the solution speed of the algorithm, which makes up for the deficiency of the parallelization research of the algorithm. Hindawi 2022-03-29 /pmc/articles/PMC8983212/ /pubmed/35392048 http://dx.doi.org/10.1155/2022/6467086 Text en Copyright © 2022 Bing Lu and Chunlei Zhou. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Lu, Bing Zhou, Chunlei Particle Swarm Algorithm and Its Application in Tourism Route Design and Optimization |
title | Particle Swarm Algorithm and Its Application in Tourism Route Design and Optimization |
title_full | Particle Swarm Algorithm and Its Application in Tourism Route Design and Optimization |
title_fullStr | Particle Swarm Algorithm and Its Application in Tourism Route Design and Optimization |
title_full_unstemmed | Particle Swarm Algorithm and Its Application in Tourism Route Design and Optimization |
title_short | Particle Swarm Algorithm and Its Application in Tourism Route Design and Optimization |
title_sort | particle swarm algorithm and its application in tourism route design and optimization |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8983212/ https://www.ncbi.nlm.nih.gov/pubmed/35392048 http://dx.doi.org/10.1155/2022/6467086 |
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