Deep reinforcement learning based optimization of automated guided vehicle time and energy consumption in a container terminal

Deep reinforcement learning based optimization of automated guided vehicle time and energy consumption in a container terminal

The energy efficiency of port container terminal equipment and the reduction of CO2 emissions are among one of the biggest challenges facing every seaport in the world. The article presents the modeling of the container transportation process in a terminal from the quay crane to the stack using batt...

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Bibliographic Details
Main Authors: Darius Drungilas, Mindaugas Kurmis, Audrius Senulis, Zydrunas Lukosius, Arunas Andziulis, Jolanta Januteniene, Marijonas Bogdevicius, Valdas Jankunas, Miroslav Voznak
Format: Article
Language:English
Published: Elsevier 2023-03-01
Series:Alexandria Engineering Journal
Subjects:
Automated guided vehicle (AGV)
Container terminal
Energy consumption
Deep reinforcement learning
Modeling
Optimization
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016822008419

Internet

http://www.sciencedirect.com/science/article/pii/S1110016822008419

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