LAUSR

ABSTRACT This article presents a method for multiobjective optimization of a complex system, modelling it as a collection of components and resource flows between them. Constraints can be imposed on a component basis or system-wide, based on the resource flows. Optimization is performed by a genetic algorithm utilizing a variable-length genome. This specialized genome enables a more open-ended design capability than previous similar frameworks. Systems are evaluated through a user-defined simulation, and results can be presented in any trade space of interest based on the performance in the simulation. The framework is then applied to the design of a table as a simple proof of concept. In this problem, the framework was found to identify a design within 4% of the theoretical optimum 80% of the time, and within 8% of the theoretical optimum the remaining 20% of the time.