A Scalable Reinforcement Learning Algorithm for Scheduling Railway Lines

This paper describes an algorithm for scheduling bidirectional railway lines (both single- and multi-track) using a reinforcement learning (RL) approach. The goal is to define the track allocations and arrival/departure times for all trains on the line, given their initial positions, priority, halt...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems Jg. 20; H. 2; S. 727 - 736
1. Verfasser:	Khadilkar, Harshad
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.02.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Allocations Decoupling Delays Heuristic methods Learning (artificial intelligence) Machine learning Processor scheduling Production scheduling Rail transportation Schedules Scheduling Tracking Trains
ISSN:	1524-9050, 1558-0016
Online-Zugang:	Volltext
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