A goal-programming enhanced collaborative optimization approach to reducing lifecyle costs for naval vessels
Understanding the trade-offs involved in assessing lifetime cost for engineering systems requires understanding trends in various engineering disciplines that require significantly different analysis methods to efficiently explore. The corresponding design spaces can be flat, defined by weak minima, and thus difficult to understand using traditixonal optimization methods. This paper presents a new multi-disciplinary framework that uses a goal-programming enhanced multi-objective collaborative optimization (eMOCO) approach to facilitate the development of the spaces. In order to further increase its efficiency in discrete or flat spaces well-suited to evolutionary optimization a unique discipline level genetic algorithm is proposed. Naval vessels are an example of an engineering system that has a difficult design space with respect to lifetime cost, however, one where it is critical to understand. As these costs are increasing, they are becoming limiting factors in a vessel's operational life. Though they are so important, the interaction between different cost categories such as production and operation has not been explored in depth and is not always clear. Understanding the trade-offs between different aspects of a vessel's total ownership costs early in the design stage can aid in the production of new ships where they are minimized. The proposed framework is verified on mathematical problems, and then used to develop trade-spaces between resistance and production for a nominal naval combatant vessel. These trade-spaces show both the knowledge gained by designers in understanding these trade-offs and the ability of the proposed eMOCO framework to develop them effectively.