An Eco-Friendly Tourism Trip Planner Driven by Z-Number Uncertainty: Evidence from Baku, Dubai, Abu Dhabi, Tashkent, and Istanbul
This paper developed an eco-friendly tourism itinerary generator that models travel times and user ratings using Z-numbers derived from departure-hour routing data and total review counts. Using an adaptive large neighborhood search algorithm, the authors benchmarked the system against a crisp-mean planner across 15 points of interest in Baku, Dubai, Abu Dhabi, Tashkent, and Istanbul over 150 seed-paired runs. The proposed method reduced average trip carbon emissions by 19.3% (from 3.24 to 2.61 kg) and total travel time by 11.5% (from 123 to 109 minutes).
Why it matters — It replaces exact-value assumptions in travel recommendation systems with uncertainty-aware fuzzy reliability, establishing that accounting for travel-time variance and rating volume directly lowers carbon emissions and transit duration.
Caveat: Because all evaluated points of interest had over 3,000 reviews, rating reliability remained uniform across the sample, and performance improvements varied substantially by city spatial structure.