Assessment of the Influence of Grid Resolution on CO2 Reduction in Route Optimization Services Using Reinforcement Learning

Mohammad Hossein Moradi (), Martin Brutsche (), Markus Wenig (), Uwe Wagner () and Thomas Koch ()
Additional contact information
Mohammad Hossein Moradi: Karlsruhe Institute of Technology
Martin Brutsche: Winterthur Gas & Diesel Ltd.
Markus Wenig: Winterthur Gas & Diesel Ltd.
Uwe Wagner: Karlsruhe Institute of Technology
Thomas Koch: Karlsruhe Institute of Technology

A chapter in Smart Services Summit, 2023, pp 65-73 from Springer

Abstract: Abstract Following the Paris Climate Agreement, the maritime industry has committed to reducing its GHG emissions by 50% by 2050 (compared to 2008). In this sense, the present work pursues this goal by focusing on an improved route optimization method using Reinforcement Learning (RL). A detailed comparison between RL and the conventional approach is carried out in this study. Besides RL, Dynamic Programming (DP) is also used to establish the benchmark. The influence of different grid resolutions and dynamic weather on effective CO2 reduction is analyzed. It is observed that these two aspects can play a significant role in the route optimization results. Furthermore, the results show that RL as a model-free approach offers a great advantage for these considerations.

Keywords: Marine route; Optimization; CO2 reduction; Reinforcement learning; Artificial intelligence; Grid resolution (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-031-36698-7_7

Ordering information: This item can be ordered from
http://www.springer.com/9783031366987

DOI: 10.1007/978-3-031-36698-7_7

Access Statistics for this chapter

More chapters in Progress in IS from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().