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2024 | OriginalPaper | Chapter

Cooperative Coevolution for Cross-City Itinerary Planning

Authors : Ziyu Zhang, Peilan Xu, Zhaoguo Wang, Wenjian Luo

Published in: Intelligent Information Processing XII

Publisher: Springer Nature Switzerland

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Abstract

The itinerary planning problem plays a pivotal role in the tourism industry, involving the selection of an optimal tour route from multiple preferred points of interest (POIs) chosen by travelers while considering their diverse needs. However, as tourism expands and transportation becomes more accessible, there is a growing preference among travelers for planning single trips across multiple cities-referred to as cross-city itinerary planning. This paper introduces a novel approach, called CCIP, the cooperative coevolution framework for cross-city itinerary planning, which employs a divide-and-conquer method to automatically devise scalable cross-city itineraries, accounting for travelers’ preferences regarding time and travel choices. Experimental evaluations on real datasets from various cities in Jiangsu Province demonstrate that the proposed algorithm outperforms two classical multi-objective optimization algorithms, as measured by the HV metric.

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previous chapter A Recommendation Algorithm Based on Automatic Meta-path Generation and Relationship Aggregation
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Metadata
Title
Cooperative Coevolution for Cross-City Itinerary Planning
Authors
Ziyu Zhang
Peilan Xu
Zhaoguo Wang
Wenjian Luo
Copyright Year
2024
Book
Intelligent Information Processing XII

Print ISBN: 978-3-031-57807-6

Electronic ISBN: 978-3-031-57808-3

Copyright Year: 2024

DOI
https://doi.org/10.1007/978-3-031-57808-3_28

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