Tour Planning: A Time-Conscious End-to-End Tourist Places Recommendation System

Abstract

Tourism today plays an important role in world economies and cultural exchange, with millions of tourists traveling to places for unique experiences that fit their needs and schedules. A dynamic and complete travel recommendation system seems very much essential for this reason. Existing systems usually don’t account for users’ available time or provide a full route for multi-destination trips, resulting in less efficient and enjoyable travel experiences. This study addresses this gap by developing a "Time-Conscious Tourist Places Recommendation System" that optimizes routes based on user preferences, available time, starting location, and desired end destination. Using data from 13,813 tourist spots across Bangladesh, the system applies several optimization algorithms, including Dijkstra's for shortest path and a Knapsack optimization algorithm, which scored the highest in our tests. Based on its performance, we selected the Knapsack algorithm as the final choice for optimizing travel routes under time constraints. Results show that the system significantly improves travel planning by suggesting routes that maximize user satisfaction within given time limits. This tool is valuable for travelers and tourism agencies seeking more efficient itinerary planning. By focusing on time-aware, end-to-end route planning, this project fills a major gap in current systems, providing a new and practical solution for organized travel.