2024/10/17 by Yiquan Wang, Wang, Yiquan · 1 citation
Computer Science · Engineering · #Artificial Intelligence (cs.AI) #Data Management and Algorithms #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Simulation and Modeling Applications #Web Applications and Data Management
paper · pdf · doi:10.48550/arxiv.2410.13226
openalex publication_date 2024/10/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The route planning problem based on the greedy algorithm represents a method of identifying the optimal or near-optimal route between a given start point and end point. In this paper, the PCA method is employed initially to downscale the city evaluation indexes, extract the key principal components, and then downscale the data using the KMO and TOPSIS algorithms, all of which are based on the MindSpore framework. Secondly, for the dataset that does not pass the KMO test, the entropy weight method and TOPSIS method will be employed for comprehensive evaluation. Finally, a route planning algorithm is proposed and optimised based on the greedy algorithm, which provides personalised route customisation according to the different needs of tourists. In addition, the local travelling efficiency, the time required to visit tourist attractions and the necessary daily breaks are considered in order to reduce the cost and avoid falling into the locally optimal solution.