A Monte Carlo approach to the ship-centric Markov decision process for analyzing decisions over converting a containership to LNG power. (15th January 2017) - Kana, Austin A.; Harrison, Brandon M.
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. Abstract : Highlights: Propose a model to study the decision to convert to LNG fuel for a container ship. New method applies Monte Carlo simulations to ship-centric Markov decision process. Propose a new metric to define model convergence within this new model. Model includes uncertainties in regulation, economics, and technology development. Studied sensitivities of ECA regulations, fuel supply chain risk, and fuel price.