Inclusion of hybrid algorithm in optimal operations of liquefied natural gas transfer arm under uncertainty

Abstract

Liquefied natural gas (LNG) transfer arms have been in regular operations due to rapid increase in the demand of an LNG. The LNG transfer arms are used in loading and unloading of the LNG to ships and onshore tanks. Best safety practises need to be put in place for effective operations of the transfer arms. The cost of carrying out such exercise must be considered for industrial benefit. Therefore, an investigation of the cost of implementation of safety improvement measures (SIMs) for optimal operations of an LNG transfer arm need to be carried out under uncertainty. Such SIMs can be used in protection of the environment and ship crew members. A model that is made of a hybridised algorithm such as fuzzy logic and evidential reasoning (ER) is employed for the exercise. The model is used to capture all the necessary information that is needed in addressing uncertainties associated with the costs of application of the SIMs. The mechanisms of the ER algorithm such as aggregation of multiple ideas to a single level are incorporated into intelligent decision system software to facilitate identification of a SIM that can optimise the LNG transfer arm operations in a cost effective manner.