A Monte Carlo Tree Search for the Optimisation of Flight Connections

Arnaud Da Silva, Ahmed Kheiri

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

In 2017, Kiwi.com proposed the Travelling Salesman Problem 2.0. Despite some similarities with the classic Travelling Salesman Problem (TSP), the problem is more complex. It can be characterised as an asymmetric, time-constrained and generalised TSP. Moreover, infeasibility further complicates the challenge, as no flights may be available between certain airports on specific days. Exact methods often fail in solving these NP -Hard problems. Therefore, alternative approaches, such as heuristics, are typically favoured. A Monte Carlo Tree Search (MCTS) is implemented to tackle Kiwi's problem, an algorithm traditionally used in board games but adapted here for air travel optimisation. The MCTS has been chosen for its proven effectiveness in handling complex and high-dimensional search spaces.
Original languageEnglish
Title of host publication2024 International Conference on Decision Aid Sciences and Applications (DASA)
PublisherIEEE
Pages1-5
Number of pages5
ISBN (Electronic)9798350369106
ISBN (Print)9798350369113
DOIs
Publication statusPublished - 17 Jan 2025
Event2024 International Conference on Decision Aid Sciences and Applications - Manama, Bahrain
Duration: 11 Dec 202412 Dec 2024

Conference

Conference2024 International Conference on Decision Aid Sciences and Applications
Abbreviated titleDASA 2024
Country/TerritoryBahrain
CityManama
Period11/12/2412/12/24

Keywords

  • optimisation
  • travelling salesman problem
  • Monte Carlo tree search
  • heuristic design

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