旅游景点筛选组合及旅游线路的优化算法与应用
Study on Filtering Sight Spots and Getting the Optimal Travel Route
查看参考文献16篇
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文摘
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近年来,我国的旅游业蓬勃发展,积累了大量的数据,有效地分析和理解这些数据,可以更好地服务于旅游业,并促进其健康科学地发展.鉴于此,引入几个算法对旅游点及旅游线路进行科学定制与设计,提出了利用极大团对旅游点进行筛选组合的新算法,同时对建立国内旅游查询系统的可行性及系统背后的算法进行了分析.实验结果表明,所提出的算法适合大规模问题,可对旅游及科研部门制定宏观策略提供参考,同时建立国内旅游查询系统也是可行的,即自驾游者可随时上网或用手机查询国内的最佳旅游景点组合,旅游线路及驾车路线,也可查询国内任意两点间的最短行车路线和任一座城市的任两点间的最优公交乘车路线,这将大大方便人们的生活 |
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其他语种文摘
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In the past two decades, along with the fast development of computer technology, high performance computing was applied to lots of scientific and engineering fields and resulted in significant breakthroughs. For example, successful decode of DNA in biology, oil exploration in geography etc., all of which could not proceed so well without the help of high performance computing. Tourism businesses are developing very fast in China, more and more new tourist attractions are coming out in many places. In the meanwhile,it accumulated a large amount of data these several years. How to efficiently analyze and correctly understand these data becomes an interesting topic. When people travel, they often need to search for the optimal combination of sight spots and the corresponding best travel tour, the shortest driving directions in detail between any two points, the best bus path between any two points in a city, and so on. Now people can get from travel agency or search online in the web for tourism route, but these routes are usually not optimal and made from experiences. There are also some services for people to search for the bus path in a city, but this is often limited, and does not work for any two points in a city. For the shortest driving directions between any two points,we still do not have this kind of services in the range of whole country, though people in U.S.are used to searching online for driving directions before going out..In this paper,we try to solve all these problems. We propose several algorithms to design the optimal combination of sight spots by filtering tourist attractions, and the main method is by listing all maximal cliques. We then compute the optimal travel route on this combination. This will then help people to choose their attraction spots to visit and get the best tour. For other problems which people often encounter in travelling such as how to get the shortest driving directions between any two points, and optimal bus path when using public transportations,we discuss the existing algorithms and propose the practical solutions. All algorithms proposed in this paper are suitable for large scale settings such as applying to millions of tourism sight spots to list all optimal tours etc. The key point is to deal with very large amount of data, for which we must adopt high performance computing. In the end of the paper, computational results are discussed and concluded that our algorithms and designs are suitable for real applications, this will make it much easier for peoples' life |
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来源
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地球信息科学学报
,2010,12(5):668-673 【扩展库】
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关键词
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旅游点组合
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旅游线路
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大规模计算
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最短路问题
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地址
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1.
山东经济学院统计与数学学院, 济南, 250014
2.
山东师范大学人口·资源与环境学院, 济南, 250014
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1560-8999 |
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学科
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自然地理学 |
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基金
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国家自然科学基金项目
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文献收藏号
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CSCD:4100224
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