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The concept of genetic algorithm (GA) is used to model the cost of maintenance and repair of a liquefied natural gas (LNG) containment system and its transfer arm, after assessing the total risk of the systems using the probabilistic risk assessment technique. The failure frequency data of the basic events of the fault tree developed to model the LNG containment system and transfer arm, which is implemented and evaluated to estimate the failure frequencies of the systems, are derived from a careful literature search. A total risk formula is developed, which is dependent on hazard severity weight, failure frequencies, and the time and cost of maintenance and repair of the LNG carrier systems. The formula serves as the objective function, while new total cost allocated for the maintenance and repair of the LNG carrier systems as a whole is the constraint with the boundaries of presenting initial/unit cost of maintenance and repair of each containment system and transfer arm. Optimization is carried out on the objective function and its constraint for the identification of new cost of maintaining and repairing the containment system and transfer arm independently with the powerful tool of GA using Matlab version 7.7 software for improvement of the system's safety level.

Fault tree analysis is a known methodology used for analysing engineering systems. The approach is usually conducted using known failure data. Given that most maritime operations are conducted in a challenging and uncertain environment, their failure data are usually unavailable requiring a flexible and yet robust algorithm for the analysis of the systems. This research therefore seeks to analyse hazards of ships during ship and port interface operations as a result of manoeuvring by incorporating fuzzy fault tree analysis method to optimise the performance effectiveness of the system. Fuzzy set theory provides the needed flexibility to represent vague information from the analysis process. The methodology is structured in such a manner that diverse sets of data can be integrated and synthesised for analysing the system. It is envisaged that the proposed method could avail safety specialist with a simple and a step-by-step framework for evaluating maritime hazards in seaport operations in a concise way.

In this research, the safety/risk level of a liquefied natural gas (LNG) carrier system is investigated through the application of a fuzzy evidential reasoning (FER) method to uncertainty treatment of its failure modes. A fuzzy set manipulation formula with multiple parameters such as consequence severity, failure consequence probability, and failure likelihood is used to assess the safety/risk levels of failure modes of the system. Such failure estimations are synthesized to evaluate the whole system’s safety/risk level using an evidential reasoning (ER) approach. Risk control options (RCOs) are developed for reduction/control of high-risk level of the system. The best RCO, which is the one with the highest preference degree, is used to improve the safety level of the system.

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