Application of uncertainty optimization based on interval programming in ship hull SBD optimal design

In the process of ship hull optimal design with SBD (simulation based design) technology, approximate model is necessary for high precision CFD (computational fluid dynamics) solver simulation. On one hand, establishment of very high precision approximation model costs computation time excessively, on the other hand, low precision leads to the uncertainty cognition of the objective function. In order to resolve this contradiction, uncertainty optimization method was introduced. Uncertainty of approximate model built by neural network was depicted by interval number. Then the minimum resistance optimization model with principal dimensions and form coefficients as design variables was established. Double nested optimization structure was used. The outer layer used IPSO (improved particle swarm optimization) algorithm to optimize the objective with penalty function, and the inner layer used MVFSA (modified very fast simulated annealing) to solve the objective function interval of the uncertainty region of wave resistance coefficient approximate model. Cases calculation shows the superiority of uncertainty optimization method and applicability of the two optimization algorithm. © 2016, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.