Evolutionary system design using a generalized component–resource model

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.

Keywords:

• Evolutionary optimization
• component selection
• complex systems
• complex optimization
• genetic algorithm

Acknowledgments

The authors would like to thank the rest of the members of the Space Power and Propulsion Lab and the Center for Orbital Debris Education and Research who assisted in this work and provided advice and feedback.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Science Foundation Graduate Research Fellowship [grant number DGE1322106].