Trip Sage-BERT:Multi-Constraint Travel Itinerary Optimization via Bidirectional Transformers and Heuristic Pathfinding

The need to plan travel intelligently, in a personalized and cost-efficient way has grown with the rapid evolution of digital tourism, as well as an increased dependence on online travel portals. The traditional itinerary planning can often be very time-consuming in terms of manual research through various websites, does not update itself in accordance with real-time, and cannot provide personalized advice based on the tastes and budgets of the individual traveler and the duration of the trip. To address these limitations, this project introduces an AI-based Smart Itinerary Generator and Budget Planner that simplifies and automates the whole vacation planning procedure. The proposed system compares the profiles of users, their interests, budgets, and contextual constraints such as seasonal changes and local events with the help of machine learning methods, natural language processing (NLP), and rule-based optimization. The model generates dynamically generated itineraries including price estimates, sequence of preferred activities, accommodation, along with providing intra-city transportation recommendations by combining external APIs, including flights, hotels, weather forecasts, maps, transit, and local attraction databases. The system will use feedback loops and adaptive ranking algorithms to continuously enhance outputs, making it more accurate and customized as time goes on. Moreover, depending on the goals set by the user, the budget planner feature offers lower-cost or high-cost alternatives as it computes detailed expenditure plans on travel, accommodation, meals and activities. The resulting itinerary, interactive maps, cost summaries, and real-time updates are displayed in a convenient dashboard, thus being applicable to both regular travelers and casual travelers. The proposed project will transform the conventional travel planning into an automated, highly adaptable, and smooth procedure through a combination of AI-based prediction, data fusion, and intelligent recommendation systems. This will enhance user satisfaction, reduce the amount of planning and allow smarter travel choices.