An AI-Agent Platform for Sustainable and Budget-Friendly Travel Planning

We introduced an agent-based system for automated, sustainable, and budget-friendly travel planning using multi-objective optimization. Specialized agents (Cost, Environmental, Personalization, and Coordination) provide a holistic approach to the challenges of modern travel planning. Evaluation demonstrates an average 15% reduction in emissions over price-only optimization while keeping cost increases within a 10% margin. User studies validate high preference satisfaction (8.2-8.9/10), explanation comprehensibility (8.1/10), and decision confidence (84%). Computational efficiency under 30 seconds confirms real-time applicability. The modular multi-agent architecture allows independent refinement of each component, and the integration of LLMs bridges the gap between optimization output and human understanding through natural-language explanations, demonstrating that economic and ecological objectives can be considered simultaneously.

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