Improving Mobility in Smart Cities with Intelligent Tourist Trip Planning
Improving Mobility in Smart Cities with Intelligent Tourist Trip Planning
复制标题
通过智能旅游规划改善智慧城市的流动性
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
M. Matskin
中科院分区：
文献类型：
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作者：
Petar Mrazovic;J. Larriba;M. Matskin
选择最有趣的旅游景点和规划最佳的观光图尔斯旅游可以是一个艰巨的任务，为个人访问不熟悉的旅游目的地。另一方面，大城市的大量游客可能会使某些地区崩溃，造成交通效率低下，经济增长不平衡以及游客和市民之间的滋扰。因此，旅游行程规划问题应考虑到城市政府管理城市环境，实现平衡和可持续发展的可能性。在本文中，我们介绍了旅游行程规划问题，其中包括个人（游客）和全球（城市）的需求。规划问题被建模为一个扩展的混合定向越野问题，可以控制部署的流动性政策，把限制点的利益和路线之间。我们提出了一种算法方法和软件工具来解决这个困难的组合优化问题，使用可变邻域搜索。所提出的算法和工具的性能进行评估，在现实生活中的数据集相关的巴塞罗那市。计算结果证实了该算法的效率和帮助个人规划旅行和城市政府实现可持续移动目标的能力。
Selecting the most interesting tourist attractions and planning optimal sightseeing tours can be a difficult task for individuals visiting unfamiliar tourist destinations. On the other hand, the massive amounts of tourists in big cities can collapse certain areas causing transport inefficiency, unbalanced economic growth and nuisance among tourists and citizens. Therefore, the tourist trip planning problem should take into account the possibility for the city government to manage the urban environment and achieve a balanced and sustainable growth. In this paper we introduce the tourist trip planning problem which covers both individual (tourist) and global (city) needs. The planning problem is modelled as an extension of the mixed orienteering problem and can be controlled by deployment of mobility policies which put restrictions on points of interest and routes between them. We propose an algorithmic approach and a software tool to solve this hard combinatorial optimisation problem using variable neighbourhood search. The performance of the proposed algorithm and the tool is assessed over a real-life dataset related to the city of Barcelona. Computational results confirm the efficiency of the algorithm and ability to help both individuals in planning their trips and city governments in achieving sustainable mobility objectives.