Optimizing using Parametric Modification Functions and Global Optimization Methods

摘要

The focus of the paper is on the development of a designer friendly hull form parameterization and its coupling with a local and a global optimization algorithms: the well known, Sequential Quadratic Programming (SQP) and the more recent evolutionary Particle Swarm Optimization (PSO). These two algorithms are representative of classes with rather opposite characteristics (derivative-based and derivative-free, respectively) and their relative performances in solving some typical ship design optimization problem will be discussed in the paper. Following a well known naval architect's design practice, a parametric* modification tool is developed for modifying the ship's geometry. The original geometry can be easily deformed by direct selection of some standard design parameters and useful information about the effect of the changing in the parameters are immediately obtained and visualized. At the same time, design parameters are assumed as design variables in the formulation of the optimization problem. In the examples, both potential flow and RANS solvers have been used. Numerical results for both single and multiobjective-problems are presented.