湖北农业科学 ›› 2021, Vol. 60 ›› Issue (9): 127-130.doi: 10.14088/j.cnki.issn0439-8114.2021.09.026

• 信息工程 • 上一篇    下一篇

基于蚁群算法的智慧旅游路线规划方案分析

王毅菲   

  1. 西安翻译学院,西安 710105
  • 收稿日期:2020-07-07 发布日期:2021-05-14
  • 作者简介:王毅菲(1984-),女,陕西西安人,副教授,硕士,主要从事旅游管理研究,(电话)13853538470(电子信箱)jiangge1007@163.com。
  • 基金资助:
    陕西省社会科学基金项目(2019S022)

Analysis of smart tourism route planning scheme based on ant colony algorithm

WANG Yi-fei   

  1. Xi′an Fanyi University,Xi′an 710105,China
  • Received:2020-07-07 Published:2021-05-14

摘要: 为了改善传统的旅游路线规划费时费力、用户体验感较差的现状,基于科技力量的智慧旅游路线规划应运而生,提出一种基于蚁群算法的智慧旅游路线规划方案。首先通过描述蚁群算法的基本原理,改善基本的蚁群算法花费时间长、容易陷入死局的缺点,对基本的蚁群算法进行改进,与基本蚁群算法相比,增加了搜索范围集中化阶段、实时更新信息素阶段、信息素回滚机制阶段。然后以旅游花费更少的钱、得到最大最舒适的旅游体验为目标,将费用目标、体验感目标进行综合,建立了基于蚁群算法的旅游路线规划模型,并利用改进的蚁群算法对规划模型进行求解。最后将模型应用于实际案例中,通过计算分析得到符合要求的最优旅游路径。

关键词: 蚁群算法, 智慧旅游, 最优路径

Abstract: In order to improve the traditional travel route planning, it takes time and effort, and the user experience is poor. This paper proposes a smart tourism route planning scheme based on ant colony algorithm. First, by describing the basic principles of the ant colony algorithm, the improvement of the basic ant colony algorithm takes a long time, and it is easy to fall into the shortcomings. The basic ant colony algorithm is improved. Compared with the basic ant colony algorithm, the range of search elements is increased. The stage of quantification, the stage of real-time update of pheromone, and the stage of pheromone rollback mechanism. Then, with the goal of spending less money on travel and getting the largest and most comfortable travel experience, the cost target and the sense of experience target are synthesized, and a travel route planning model based on ant colony algorithm is established, and the improved ant colony algorithm is used to planning model to solve. Finally, the model is applied to actual cases, and the optimal travel path that meets the requirements is obtained through calculation and analysis.

Key words: ant colony algorithm, smart tourism, optimal path

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