| 基于蚁群算法的旅游路线优化方案 |
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| 引用本文： | 李艳春,陈锦太.基于蚁群算法的旅游路线优化方案[J].教育技术导刊,2009,8(9):89-92. |
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| 作者姓名： | 李艳春 陈锦太 |
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| 作者单位： | 浙江科技学院 信息与电子工程学院，浙江 杭州 310023 |
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| 基金项目： | 浙江省自然科学基金青年基金项目（LQ20F020010） |
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| 摘 要： | 在传统旅游路径规划中，通常将问题抽象成旅行商问题（TSP）进行讨论，该方法仅考虑消耗时间最短的路径，忽视了景点当前热度、拥挤程度等诸多影响旅客旅游体验的因素。为了给旅客带来更好的旅游体验，综合考虑上述因素，对蚁群算法作出改进。改进后算法以交通时间更短、导向旅游体验好的景点为目标函数，根据各景点当前热度、拥挤度及景点与景点间路径交通状况对景区内各路径赋以合理的权重，从而规划出合理路径。实验结果表明，改进后的蚁群算法可综合考虑更多影响旅客旅游体验的因素，从而使规划出的旅游路径为旅客带来更良好的旅游体验。
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| 关 键 词： | 旅游路径规划 蚁群算法 旅行商问题 |
| 收稿时间： | 2020-03-08 |
Reasearch on Tourism Route Planning Based on Ant Colony Algorithm |
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| XU Shu-yang,PAN Hua-zheng,WANG Hai-jiang.Reasearch on Tourism Route Planning Based on Ant Colony Algorithm[J].Introduction of Educational Technology,2009,8(9):89-92. |
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| Authors: | XU Shu-yang PAN Hua-zheng WANG Hai-jiang |
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| Institution: | School of Information and Electronic Engineering，Zhejiang University of Science and Technology，Hangzhou 310023，China |
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| Abstract: | In traditional travel route planning，the problem is usually abstracted into a traveling salesman problem（TSP）for discussion，and the method only considers the route that consumes the shortest time，and many factors that affect the tourists’travel experience such as the current popularity of the attractions and the current crowding degree of the attractions are ignored. In order to bring a better travel experience for tourists，the ant colony algorithm is improved by comprehensively considering the above factors. The improved algorithm takes shortened traffic time and guided tourist spots with good tourist experience as the objective functions，reasonable weights to each route in the scenic spot are given according to the current heat，congestion of the scenic spots and the traffic conditions of the scenic spots to make a reasonable route plan. The experimental results show that the improved ant colony algorithm can comprehensively consider more factors that affect the travelers’travel experience，so that the planned travel route can bring a better travel experience to travelers. |
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| Keywords: | tourism route planning ant colony algorithm traveling salesman problem |
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