ULTIMATE LIMIT STATE BASED SHIP STRUCTURAL DESIGN USING MULTI-OBJECTIVE DISCRETE PARTICLE SWARM OPTIMIZATION

摘要

Multi-objective optimization problems consist of several objectives that must be handled simultaneously. These objectives usually conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. A reasonable solution to a multi-objective problem is to investigate a set of solutions, each of which satisfies the objectives at an acceptable level without being dominated by any other solution. Genetic or evolution algorithms have been demonstrated to be particularly effective to determine excellent solutions to these problems. Among many algorithms, the particle swarm optimization (PSO) has been found to be faster with less computational overhead. In this paper a multi-objective discrete particle swarm optimization is formulated and used to optimize a large and complex thin-wall structure on the basis of weight, safety and cost. The structure weight and cost are calculated using realistic finite element models. The design process has two stages: (1) the actual stresses are obtained by finite element analysis of the full ship, (2) for a midship segment of the ship (referred to as a "control cluster") the structural safety is evaluated using the ALPS/ULSAP set of ultimate limit state criteria, and then the segment is optimized using any suitable optimization method (in this paper, the PSO method). Both stages involve iteration, but the process is arranged so as to keep the number of full ship finite element analyses to a minimum. The complete design process is illustrated for a 200,000 ton oil tanker. The numerical results show that the PSO method is very useful to perform ultimate strength based ship structural optimization with multi-objectives, namely minimization of the structural weight and cost and maximization of structural safety. The example also demonstrates that the proper definition of boundary conditions and design load cases is of paramount importance for design optimization.