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Changing Subsystem Information Strategies Using Weighted Objectives: Increasing Robustness to Biased Information Passing

[+] Author Affiliations
Jesse Austin-Breneman, Bo Yang Yu, Maria C. Yang

Massachusetts Institute of Technology, Cambridge, MA

Paper No. DETC2015-47667, pp. V02AT03A023; 11 pages
doi:10.1115/DETC2015-47667
From:
  • ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2A: 41st Design Automation Conference
  • Boston, Massachusetts, USA, August 2–5, 2015
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5707-6
  • Copyright © 2015 by ASME

abstract

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.

Copyright © 2015 by ASME
Topics: Robustness

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