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...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Darius Drungilas, Mindaugas Kurmis, Audrius Senulis, Zydrunas Lukosius, Arunas Andziulis, Jolanta Januteniene, Marijonas Bogdevicius, Valdas Jankunas, Miroslav Voznak
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	Elsevier 2023-03-01
Sarja:	Alexandria Engineering Journal
Aiheet:	Automated guided vehicle (AGV) Container terminal Energy consumption Deep reinforcement learning Modeling Optimization
Linkit:	http://www.sciencedirect.com/science/article/pii/S1110016822008419
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