Global Optimization of Fast Vessels

In the last decade, growing attention has been paid on Numerical Optimization in the naval eld. Dierent papers have been presented related to a wide range of applications, ranging from building cost of a ship to their hydrodynamic and structural characteristics. All these problem are highly constrained, and the optimal solution is dicult to nd due to the nature of the problem itself. To attacks these problems, designers will give attention to Global Optimization (GO) in the next few years. Indeed, a simple local optimizer could be not enough: in fact, local methods usually applied are easily trapped by local minimizers and stuck in their basin of attraction. In such a situation, we have no idea about the extra improvement we could have obtained if, i.e. a dierent starting point were adopted. On the other hand, GO algorithms try to nd the global optimum of the objective function, assuring that no more improvements can be obtained for the so formulated optimization problem, regardless to the starting point. In this paper some classical Derivative-Free methods are applied to the optimization of a fast ship and compared with some original GO methods, like a Multistart Gradient Method (MsGM), the Particle Swarm Optimization (PSO) method and the Diagonal Rectangular Algorithm for Global Optimization (DRAGO) method [9].