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dc.contributor.authorAustin-Breneman, Jesse
dc.contributor.authorYu, Bo Yang
dc.contributor.authorYang, Maria C.
dc.date.accessioned2019-01-14T18:26:11Z
dc.date.available2019-01-14T18:26:11Z
dc.date.issued2015-08
dc.identifier.isbn978-0-7918-5707-6
dc.identifier.urihttp://hdl.handle.net/1721.1/120029
dc.description.abstractComplex 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.en_US
dc.description.sponsorshipUniversity of Alabama in Huntsville. System Engineering Consortiumen_US
dc.description.sponsorshipNational Science Foundation (U.S.). Graduate Research Fellowshipen_US
dc.publisherASME Internationalen_US
dc.relation.isversionofhttp://dx.doi.org/10.1115/DETC2015-47667en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceASMEen_US
dc.titleChanging Subsystem Information Strategies Using Weighted Objectives: Increasing Robustness to Biased Information Passingen_US
dc.typeArticleen_US
dc.identifier.citationAustin-Breneman, Jesse, Bo Yang Yu, and Maria C. Yang. “Changing Subsystem Information Strategies Using Weighted Objectives: Increasing Robustness to Biased Information Passing.” Volume 2A: 41st Design Automation Conference (August 2, 2015).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Ocean Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Societyen_US
dc.contributor.departmentMIT Edgerton Centeren_US
dc.contributor.mitauthorAustin-Breneman, Jesse
dc.contributor.mitauthorYu, Bo Yang
dc.contributor.mitauthorYang, Maria
dc.relation.journalVolume 2A: 41st Design Automation Conferenceen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-01-14T18:04:25Z
dspace.orderedauthorsAustin-Breneman, Jesse; Yu, Bo Yang; Yang, Maria C.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-7891-1187
dc.identifier.orcidhttps://orcid.org/0000-0002-7776-3423
mit.licensePUBLISHER_POLICYen_US


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