Flying tourist problem: Flight time and cost minimization in complex routes

Abstract

This work introduces and formalizes the Flying Tourist Problem (FTP), whose goal is to find the best schedule, route, and set of flights for any given unconstrained multi-city flight request. To solve the FTP, the developed work proposes a methodology that allows an efficient resolution of this rather demanding problem. This strategy uses different heuristics and meta-heuristic optimization algorithms, allowing the identification of solutions in real-time, even for large problem instances. The implemented system was evaluated using different criteria, including the provided gains (in terms of total flight price and duration) and its performance compared to other similar systems. The obtained results show that the developed optimization system consistently presents solutions that are up to 35% cheaper (or 60% faster) than those developed by simpler heuristics. Furthermore, when comparing the developed system to the only publicly available (but not-disclosed) alternative for flight search, it was shown that it provides the best-recommended and the cheapest solutions, respectively 74% and 95% of the times, allowing the user to save time and money.