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Improved On-Demand Travel Route Planning Model with Interest Fields.
1Zhengzhou University of Science and Technology, Zhengzhou 450000, China.
Computational Intelligence and Neuroscience
|August 19, 2022
Summary
This study introduces an improved model for intelligent tourism route planning, enhancing personalization by considering tourist interests. The new approach offers shorter, more cost-effective travel routes compared to traditional methods.
Area of Science:
- Artificial Intelligence
- Tourism Management
Background:
- Current tourism route planning suffers from subjectivity and lacks personalization.
- Intelligent tourism route planning is crucial for smart tourism development.
Purpose of the Study:
- To propose an improved interest field travel route planning model.
- To address limitations of existing subjective and impersonal tourism route planning.
Main Methods:
- Developed an intelligent interest field extraction model.
- Designed an improved greedy algorithm for enhanced solution accuracy and local search.
- Established a motivated iterative value output model for route planning.
Main Results:
- The proposed model generates shorter and less expensive routes.
- Iterative analysis provides optimal and suboptimal routes based on tourist motivations.
- Demonstrated improved route planning accuracy and efficiency.
Conclusions:
- The model offers a feasible and significant advancement for smart tourism route planning.
- Personalized route planning based on tourist interests is effectively achieved.
- The approach enhances the practical application of intelligent systems in tourism.
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