With the improvement of people’s living standards and the desire to pursue quality of travel, the number of people who choose self-guided itineraries is increasing sharply. However, the problem is that planning routes during the trip are exhausting, and the efficiency of transportation. In response to this and considering the psychology of people making the most of their holidays along with current boom in chain travel, the paper proposes a frame and an algorithm that aims to optimize the travel route. This paper studies route planning for chain travel of city groups within a specific range based on cluster analysis. The algorithm refers to the solution of TSP, knowledge in Graph Theory, and is suitable for optimizing travel itineraries for multiple cities for several days, characterized by providing users with time and money-saving options. It reduces waste on the road, waiting times for travelers, and provides convenience for self-guided itineraries.
Smart Optimization Design of Urban Group Chain Travel Routes
20th COTA International Conference of Transportation Professionals ; 2020 ; Xi’an, China (Conference Cancelled)
CICTP 2020 ; 2107-2117
2020-08-12
Conference paper
Electronic Resource
English
Smart Optimization Design of Urban Group Chain Travel Routes
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