An Integrated Framework Integrating Monte Carlo Tree Search and Supervised Learning for Train Timetabling Problem. (arXiv:2311.00971v1 [cs.LG])

The single-track railway train timetabling problem (TTP) is an important and
complex problem. This article proposes an integrated Monte Carlo Tree Search
(MCTS) computing framework that combines heuristic methods, unsupervised
learning methods, and supervised learning methods for solving TTP in discrete
action spaces. This article first describes the mathematical model and
simulation system dynamics of TTP, analyzes the characteristics of the solution
from the perspective of MCTS, and proposes some heuristic methods to improve
MCTS. This article considers these methods …

article arxiv computing framework railway search spaces supervised learning train tree unsupervised unsupervised learning