Multidisciplinary Design Optimization (MDO) is a powerful engineering tool that allows designers to incorporate information from all relevant design disciplines simultaneously. In aerospace applications, for example, MDO has been used to produce designs that incorporate both the structural and aerodynamic disciplines. It is not generally possible to optimize the objectives of all disciplines simultaneously, so producing an optimal design requires a human designer to balance the tradeoffs between the various objectives. We propose and implement a novel system that helps the designer explore the various possible tradeoffs and systematically find their most preferred design. We show that the system converges to the most preferred design in a simulated task and discuss how it could be used in an industrial MDO problem.