A Tourism Route-Planning Approach Based on Comprehensive Attractiveness

Zhang, Yanmei; Jiao, Linjie; Yu, Zhijie; Lin, Zheng; Gan, Mengjiao

doi:10.1109/access.2020.2967060

Cited by 18 publications

(12 citation statements)

References 26 publications

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“…It has a wide range of applications in scenic spots, hotels, transportation, and other aspects, which can take into account the needs of users in an all-round way. Among them, tourism route planning is an indispensable part of smart tourism research and tourism recommendation system development [18]. Relying on machine learning and deep learning, as well as the vigorous development of its supporting technologies and hardware through the development of the model, the mining and prediction accuracy of tourists' interest has been greatly improved, which will play a vital role in the rapid development and progress of smart tourism and tourism economy and also provide a platform for the development of local tourism [19].…”

Section: Introductionmentioning

confidence: 99%

Route Planning of Health Care Tourism Based on Computer Deep Learning

Wang

2022

Wireless Communications and Mobile Computing

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With the continuous improvement of people’s living standards, the form of tourism is gradually changing. In the past two years, people’s demand for tourism has also changed from traditional ornamental tourism to wellness tourism, which has provided a development opportunity for rural tourism. At the same time, the government has also begun to focus on the development of tourism with rural characteristics to promote the development of rural areas. However, health tourism still has certain defects, and the development of rural planning is still advancing and improving. Leisure agriculture is an area where agriculture, tourism, and service industries intersect, and it is the link that maintains the common development of the three. Applying the concept of health tourism to the planning and design of leisure agricultural parks can make people satisfied in tourism. The pursuit of health and wellness also drives the development of the rural economy. With the progress of the economy and the continuous improvement of people’s living standards, the traditional travel mode is gradually changing towards the direction of informatization. The traditional way of travel-by-travel agencies planning travel routes is no longer the first choice for people to travel. On the one hand, the rapid development of the Internet brings convenience to people, and on the other hand, it also brings a lot of information to the public.

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Section: Introductionmentioning

confidence: 99%

Route Planning of Health Care Tourism Based on Computer Deep Learning

Wang

2022

Wireless Communications and Mobile Computing

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“…Uwaisy et al [18] combined the results of tabu search with the concept of multiattribute utility theory to determine the optimal travel route based on popularity, cost, number of tourist attractions, and other indicators. Zhang et al [19] took into account several factors in the route recommendation, such as distance between attractions, initial travel location, initial departure time, travel duration, total cost, rating, and popularity of attractions. Meanwhile, they used the comprehensive attraction index to rank tourist routes.…”

Section: Factors In Route Recommendationmentioning

confidence: 99%

Personalized Route Recommendation with Hybrid Tabu Search Algorithm Based on Crowdsensing

Han

Zheng

Guan

et al. 2023

International Journal of Intelligent Systems

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In the postmodern era of tourism, tourists’ behavior has undergone a substantial change and the demand of customized experience dominates the tourism market. The traditional single-objective travel route recommendation method fails to meet the multiobjective needs of users. To handle this problem, a multiobjective hybrid tabu search algorithm for urban travel route recommendations is proposed in this paper. First, the rating and level of attractions, as well as the corresponding information of hotels and restaurants within a certain radius, are considered. Then, based on this information, a crowdsensing scoring method is established. Second, the hybrid particle swarm genetic optimization algorithm is exploited to generate a single-object route, and the fast nondominated Pareto sorting algorithm is exploited to find the optimized solution. Then, the hybrid tabu algorithm is used to optimize the personalized route chosen according to multiple objects set by users. This algorithm combines the global search ability of the genetic algorithm and the neighborhood search ability of the tabu algorithm to prevent convergence from falling into a local optimum. Finally, the experiments are conducted on the real-world data collected from the Dianping and Ctrip web sites. The comparison with baseline algorithms indicates that the algorithm proposed in this paper provides accurate and reasonable route recommendations for users.

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“…rough the study of the existing tourism literature, this paper discusses the key gap of knowledge in the tourism eld so as to understand the [12]. Zhang discusses the parameter setting of the weighting algorithm in solving the traveling salesman problem, and the results have a certain reference value [13]. Ying et al proposes an improved ant colony algorithm by combining the ant colony algorithm and simulated annealing algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis and Study on Intelligent Tourism Route Planning Scheme Based on Weighted Mining Algorithm

2022

Scientific Programming

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In order to study the intelligent tourism route planning scheme based on a weighted mining algorithm, firstly, a traveling salesman problem based on an improved weighted mining algorithm is proposed. Then, based on the traveling salesman problem, the constraints of travel time and driving time are added, and the mathematical model aiming at the minimum number of travel days is established. The improved weighted mining algorithm is used to solve the model: firstly, the scenic spots are divided into regions according to provinces and solved; then, the regions of some scenic spots are modified and solved again according to the solution results, and the specific itinerary is given; finally, based on the route planning problem and considering a variety of transportation modes, a double objective mathematical model with the optimal tourism cost and the best tourism experience is established. When solving, the double objective is reasonably transformed into a single objective, the model is solved by comprehensively considering the tourism cost and tourism experience, and the specific schedule is given according to the solution results.

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A Tourism Route-Planning Approach Based on Comprehensive Attractiveness

Cited by 18 publications

References 26 publications

Route Planning of Health Care Tourism Based on Computer Deep Learning

Route Planning of Health Care Tourism Based on Computer Deep Learning

Personalized Route Recommendation with Hybrid Tabu Search Algorithm Based on Crowdsensing

Analysis and Study on Intelligent Tourism Route Planning Scheme Based on Weighted Mining Algorithm

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