Multiobjective design of a marine vehicle with aid of design knowledge

Abstract

To generate the Pareto optimal set efficiently in multiobjective optimization, a hybrid optimizer is developed by coupling the genetic algorithm and the direct search method. This method determines a candidate region around the global optimum point by using the genetic algorithm, then searches the global optimum point by the direct search method concentrating in this region, thus reducing calculation time and increasing search efficiency. Although the hybrid optimizer provides cost-effectiveness, the design optimization process involves a number of tasks which require human expertise and experience. Therefore, methods of optimization and associated programs have been used mostly by experts in the real design world. Hence, this hybrid optimizer incorporates a knowledge-based system with heuristic and analytic knowledge, thereby narrowing the feasible space of the objective function. Some domain knowledge is retrieved from database and design experts. The obtained knowledge is stored in the knowledge base. The results of this paper, through application to marine vehicle design with multiobjective optimization, show that the hybrid optimizer with aid of design knowledge can be a useful tool for multiobjective optimum design. (C) 1997 by John Wiley & Sons, Ltd.