Solving multiobjective optimization problems using quasi-separable MDO formulations and analytical target cascading

1. Abstract An approach to multiobjective optimization is to define a scalar substitute objective function that aggregates all objectives and solve the resulting aggregate optimization problem (AOP). In this paper, we discern that the objective function in quasi-separable multidisciplinary design optimization (MDO) problems can be viewed as such an aggregate objective function (AOF). We consequently claim that a method that can solve quasi-separable problems can also be used to obtain Pareto points of associated AOPs. Our motivation stems from cases where AOPs are too hard to solve or when the design engineer does not have access to the models necessary to evaluate all the terms of the AOF . In this case, decomposition-based design optimization methods can be particularly useful to solve the AOP as a quasi-separable MDO problem. Specifically, we use the analytical target cascading methodology to formulate decomposed subproblems of quasi-separable MDO problems and coordinate their solution in order to obtain Pareto points of the associated AOPs. We first illustrate our approach using a well-known simple geometric programming example and then present a vehicle suspension design problem with three objectives related to ground vehicle ride and handling. 2.