Application of a genetic algorithm to the optimal structural design of a ship's engine room taking dynamic constraints into consideration

Abstract

The genetic algorithm, known as GA, is used to optimize engine room structure, not only under static constraints, but also under dynamic constraints. A penalty function method is used to handle the complicated constraint conditions based on the numerical results of dynamic and static analyses. There are several ways to take the dynamic effect into account in the optimum design of ship structure. First, the inequality constraint condition is applied to separate the natural frequency and the exciting frequency. Second, generalized design variables are introduced in order to transfer not only the dynamic but also the static equilibrium equations into the equality constraints, resulting in the optimal structural design without the need to solve these equilibrium equations. Third, the magnitudes of the acceleration and displacement are constrained instead of applying the natural frequency constraint condition. In order to achieve better convergency in the optimization with least resources, several operators and methods are considered and then introduced into the structural design of the engine room. The new operator, called either objective elitism or fitness elitism, is introduced to improve the efficiency of the method. The effect of boundary mutation and nonuniform mutation on the performance of the GA is examined. Not only binary representation but also floating-point representation are used to express the design gene in the GA. Fuzzy theory is applied in the GA to handle the uncertainty of the constraint conditions. Two ways of solving fuzzy optimization are investigated in order to obtain a fuzzy solution and a crisp solution.