AI Insight
Researchers developed an eco-friendly tourism trip planner that uses Z-numbers to represent uncertain travel times and reliability of attraction ratings, rather than treating them as exact values. Testing across five cities (Baku, Dubai, Abu Dhabi, Tashkent, and Istanbul) with 150 paired runs showed the Z-number approach reduced carbon emissions by 19.3% (from 3.24 to 2.61 kg per trip) and travel time by 11.5% (from 123 to 109 minutes) compared to a conventional baseline planner. The improvements were statistically significant for travel time in three cities and for carbon reduction in Baku, though results varied by city characteristics.
Why it matters
This approach could make tourism planning more environmentally sustainable while improving efficiency, addressing the growing need to reduce travel-related carbon emissions. The method's ability to incorporate uncertainty from real-world data (varying departure times, varying review counts) may lead to more reliable and eco-conscious trip recommendations for travelers.
⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
Abstract: Deployed tourism trip planners ingest travel times and ratings as exact numbers, although routing services return travel times that vary with the hour of departure and a platform rating may rest on a handful of reviews or on hundreds of thousands. We present an eco-friendly trip planner that represents both quantities as Z-numbers, which pair a fuzzy restriction on a value with a fuzzy reliability on the evidence behind it, and that constructs them directly from routing-service observations at six departure hours and from platform review counts rather than from linguistic elicitation. A hybrid loss combines score, carbon, travel-time, and reliability terms, and an adaptive large neighborhood search returns single-day itineraries through a conversational front end. We compare the planner with a crisp-mean baseline under an identical optimizer in Baku, Dubai, Abu Dhabi, Tashkent, and Istanbul, with fifteen points of interest and thirty seeds per city, and we evaluate the selected itineraries on their trip carbon and their total travel time. Pooled over 150 seed-paired runs, the planner lowers trip carbon from 3.24 to 2.61 kg (19.3%, Wilcoxon p = 0.017; city-clustered bootstrap interval 6.4% to 26.7%) and travel time from 123 to 109 minutes per trip (11.5%, p = 2.8e-10; interval 5.0% to 18.2%). The travel-time reductions survive a Holm correction in Baku, Istanbul, and Abu Dhabi; the carbon reduction is significant in Baku and large but uncertain in the dispersed catalogs of Dubai and Abu Dhabi; and neither metric changes in Tashkent. Review counts are estimates of at least 3,000 for every point of interest, so rating reliability does not vary, and with a single baseline, the results establish feasibility and direction rather than a general advantage. Code, routing caches, frozen routing tables, and per-seed results are openly released.