A Novel Multi-Objective and Multi-Constraint Route Recommendation Method Based on Crowd Sensing

Applied Sciences

卷:11

Siguang Chen¹  Ji Zhang²  Xiaoyao Zheng³  Yonglong Luo³  Qingying Yu³  Liping Sun³ 

[1] Engineering Research Center of Communication and Network Technology, Nanjing University of Posts and Telecommunications, Nanjing 210000, China;

[2] Faculty of Health, Engineering and Sciences, University of Southern Queensland, Toowoomba 4350, Australia;

[3] School of Computer and Information, Anhui Normal University, Wuhu 241002, China;

关键词: crowd sensing;    multi-constraint;    route recommendation;    multi-objective;   

DOI  :  10.3390/app112110497

来源: DOAJ

【 摘 要 】

Nowadays, people choose to travel in their leisure time more frequently, but fixed predetermined tour routes can barely meet people’s personalized preferences. The needs of tourists are diverse, largely personal, and possibly have multiple constraints. The traditional single-objective route planning algorithm struggles to effectively deal with such problems. In this paper, a novel multi-objective and multi-constraint tour route recommendation method is proposed. Firstly, ArcMap was used to model the actual road network. Then, we created a new interest label matching method and a utility function scoring method based on crowd sensing, and constructed a personalized multi-constraint interest model. We present a variable neighborhood search algorithm and a hybrid particle swarm genetic optimization algorithm for recommending Top-K routes. Finally, we conducted extensive experiments on public datasets. Compared with the ATP route recommendation method based on an improved ant colony algorithm, our proposed method is superior in route score, interest abundance, number of POIs, and running time.

【 授权许可】

Unknown