This paper describes a hydroinformatic model for generating a Pareto set of LNG terminal layouts that are subject to uncertainty using a multi-objective genetic algorithm. The NSGAII is used to select parameters that propagate through a bespoke LNG terminal design algorithm which includes a Monte Carlo simulator to estimate the uncertainty in each concept. This allows the trade-off between cost and risk to be explored at the earliest stage of design. The results of a case study indicate that nearshore terminals typically have lower capital costs but higher maintenance costs and more uncertainty. The paper concludes that in the example site used, locating the terminal 1000m offshore results in an optimal compromise between cost and risk.
Rustell, Michael John Francis; Orsini, Aurora; Khu, Soon-Thiam; Jin, Yaochu; and Gouldby, Ben, "Optimizing Maritime Terminal Infrastructure Subject To Uncertainty" (2014). CUNY Academic Works.