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The optimum ship hull design solution has always been a concern, and in recent years, genetic algorithms to optimise the ship hull structure have been developed. The genetic algorithm’s fundaments generate alternative solutions and compare them with pre-defined constants and objectives. The development of design solutions evolves through competition and controlled variations. Minimising the ship hull structure weight is essential in reducing the ship’s capital (construction) expenditure and increasing the cargo capacity. The risk of the ship is associated with the loss of the ship, cargo, human life, environmental pollution, etc. It is a governing factor impacted by the chosen structural design solution and the measures taken to reduce the structural weight. A genetic algorithm will be employed to study the weight minimisation of a multi-purpose ship hull structure, controlling the associated risk by accounting for several structural design variables. The risk and best design solution are defined by the probability of compressive collapse of the stiffened plates, integral ship hull structure, and the associated cost due to failure. The Pareto frontier solutions, calculated by the non-dominated sorting genetic algorithm, NSGA-II, will be employed to determine feasible solutions for the design variables. The first-order reliability method will estimate the Beta reliability index based on the topology of the stiffened plates and ship hull structure as a part of the Pareto frontier solutions. The algorithm employed will not account for any manufacturing constraints and consequences due to the encountered optimal design solution.
Koni et al. (Thu,) studied this question.