A Monte Carlo approach to the ship-centric Markov decision process for analyzing decisions over converting a containership to LNG power

Austin A. Kana, B.M. Harrison

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)
31 Downloads (Pure)

Abstract

A Monte Carlo approach to the ship-centric Markov decision process (SC-MDP) is presented for analyzing whether a container ship should convert to LNG power in the face of evolving Emission Control Area regulations. The SC-MDP model was originally developed as a means to analyze uncertain, sequential decision making problems. However, the original model is limited in its handling of uncertainty by only using discrete probabilistic values to account for the uncertainty. This paper extends the model to include Monte Carlo simulations to gain a deeper understanding of how uncertainty affects decision making behavior. A case study is presented involving the impact of evolving Emission Control Areas on the design and operation of a notional 13,000 TEU container ship. The decision of whether to invest in a dual fuel LNG engine is analyzed given uncertainties in economic parameters, regulatory scenarios, and supply chain risks. The case study is used to show how variations in uncertain parameters can have a drastic effect on optimal decision strategies.

Original languageEnglish
Pages (from-to)40-48
JournalOcean Engineering
Volume130
DOIs
Publication statusPublished - 2017

Keywords

  • Decision making
  • Emission Control Area
  • LNG
  • Markov decision process
  • Monte Carlo simulation
  • Uncertainty analysis

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