Complex system design requires managing competing objectives between many subsystems. Previous field research has demonstrated that subsystem designers may use biased information passing as a negotiation tactic and thereby reach sub-optimal system-level results due to local optimization behavior. One strategy to combat the focus on local optimization is an incentive structure that promotes system-level optimization. This paper presents a new subsystem incentive structure based on Multi-disciplinary Optimization (MDO) techniques for improving robustness of the design process to such biased information passing strategies. Results from simulations of different utility functions for a test suite of multi-objective problems quantify the system robustness to biased information passing strategies. Results show that incentivizing subsystems with this new weighted structure may decrease the error resulting from biased information passing.

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