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An Optimal Round-Trip Route Planning Method for Tourism Based on Improved Genetic Algorithm.

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  • 1College of Land and Tourism, Luoyang Normal University, Luoyang 471934, Henan, China.

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This study introduces an enhanced genetic algorithm (GA) to find the shortest tourist routes, optimizing travel plans for independent tourists. The algorithm effectively reduces travel time and expenses for visiting multiple attractions.

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Area of Science:

  • Operations Research
  • Computer Science
  • Tourism Management

Background:

  • Optimizing round-trip travel routes is crucial for independent tourists and the tourism industry.
  • Efficient route planning addresses the need for customized travel demands and business development.

Purpose of the Study:

  • To present a genetic algorithm (GA) for determining the shortest tourist route among multiple destinations.
  • To utilize an enhanced genetic algorithm (IGA) for optimal travel path planning and itinerary estimation.

Main Methods:

  • An enhanced genetic algorithm (IGA) is developed and explained.
  • The study details the model construction and solution process.
  • Simulation experiments examine the convergence of the GA for path planning.

Main Results:

  • The IGA effectively plans paths for multiple scenic locations.
  • The algorithm successfully identifies the shortest travel routes.
  • Experimental results show reduced travel expenses and saved travel time.

Conclusions:

  • The enhanced genetic algorithm (IGA) is a valuable tool for optimizing tourist travel routes.
  • The study highlights significant research and practical implications for tourism.
  • The IGA offers a robust solution for efficient and cost-effective travel planning.