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A hybrid approach to plan itinerary for tourists

机译：为游客计划行程的混合方法

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摘要

With the rapid development of information, communication and transportation systems, the number of tourists is increasing all over the world. Most of the tourists are facing problems when they visit unfamiliar places. That's why it is often difficult for an individual tourist to make an optimal sightseeing itinerary plan during a tight schedule. To help tourists in this situation, a hybrid approach has been proposed in this paper to recommend an optimal itinerary plan. In this approach, K-means clustering algorithm has been used to cluster various tourist spots based on the geographic location and preferences of the tourists. Then the individual cluster is treated as a travelling salesman problem. To find the optimal route in each cluster greedy and 2-opt algorithms are applied. To switch from one cluster to the next cluster, a route is established from the last spot of one cluster to the centroid of the next cluster. Thus, all the tourist spots will be visited efficiently.
机译：随着信息，通信和运输系统的迅速发展，世界各地的游客人数正在增加。大多数游客在不熟悉的地方都会遇到问题。这就是为什么个人游客通常难以在紧凑的行程中制定最佳的观光行程计划的原因。为了在这种情况下帮助游客，本文提出了一种混合方法来推荐最佳的行程计划。在这种方法中，已使用K均值聚类算法根据游客的地理位置和喜好对各种旅游景点进行聚类。然后，将单个集群视为旅行商问题。为了在每个群集中找到最佳路由，应用了贪婪算法和2-opt算法。要从一个群集切换到下一个群集，需要建立从一个群集的最后一个点到下一个群集的质心的路由。因此，将有效地访问所有的旅游景点。

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