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Travel Planning Optimization System Employing Genetic Algorithms with Multiple Parameters | IEEE Conference Publication | IEEE Xplore

Travel Planning Optimization System Employing Genetic Algorithms with Multiple Parameters


Abstract:

Many people around the world enjoy traveling as a popular leisure activity. The process of trip planning can be time-consuming, requiring travelers to choose between vari...Show More

Abstract:

Many people around the world enjoy traveling as a popular leisure activity. The process of trip planning can be time-consuming, requiring travelers to choose between various options and make decisions based on their preferences and interests.This paper addresses the tourist trip design problem by proposing a Travel Planning Optimization System (TPOS), which includes an architecture that employs genetic algorithms to streamline travel planning. The paper’s novelty lies in considering numerous travel factors, such as duration of visits, travel time, preferred types of locations, operating hours, destination popularity and the scheduling of places to eat in the daily program, into a single metric. This approach holds great promise in transforming travel planning by providing customized experiences that closely match the unique preferences and interests of each traveler, while using real location-related information in determining an efficient multiple-day itinerary.
Date of Conference: 10-12 October 2024
Date Added to IEEE Xplore: 11 November 2024
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Conference Location: Sinaia, Romania

References

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