Managing multi-goal design problems using adaptive leveling-weighting-clustering algorithm

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dc.contributor.authorGuo, Lin
dc.contributor.authorMilisavljevic‐Syed, Jelena
dc.contributor.authorWang, Ru
dc.contributor.authorHuang, Yu
dc.contributor.authorAllen, Janet K.
dc.contributor.authorMistree, Farrokh
dc.date.accessioned2022-10-24T17:38:52Z
dc.date.available2022-10-24T17:38:52Z
dc.date.issued2022
dc.description.abstractIn this paper, we address the issue of solving problems with multiple components, multiple objectives, and target values for each objective. There are limitations in managing these multi-component, multi-goal problems such as the need for domain expertise to combine or prioritize the goals. In this paper, we propose a domain-independent method, Adaptive Leveling-Weighting-Clustering (ALWC), to manage the exploration of design scenarios of multi-goal, engineering-design problems. Using ALWC, designers explore combinations and priorities of the goals based on their interrelationships. Through iteration, design scenarios are obtained with higher goal achievements and an improved understanding of the relationship among subsystems. This is achieved without increasing computational complexity. This knowledge is helpful for multi-component design. The ALWC method is demonstrated using a thermal-system design problem.en_US
dc.description.abstractLin Guo acknowledges Shehnaz Shaik for programming contributions. Lin Guo acknowledges the financial support from the Pietz Professorship and Start-Up Fund at the South Dakota School of Mines and Technology. Lin Guo and Janet K. Allen gratefully acknowledge the financial support from the John and Mary Moore Chair at the University of Oklahoma. Lin Guo and Farrokh Mistree gratefully acknowledge financial support from the L.A. Comp Chair at the University of Oklahoma. Ru Wang gratefully acknowledges the Project funded by China Postdoctoral Science Foundation [Grant 2018M640073]. Financial support was provided from the Office of the Vice President for Research and Partnerships and the Office of the Provost, University of Oklahoma for assistance with publication charges.en_US
dc.description.peerreviewYesen_US
dc.identifier.citationCite this article Guo, L., Milisavljevic-Syed, J., Wang, R. et al. (2022). Managing multi-goal design problems using adaptive leveling-weighting-clustering algorithm. Research in Engineering Design. https://doi.org/10.1007/s00163-022-00394-zen_US
dc.identifier.doihttps://doi.org/10.1007/s00163-022-00394-zen_US
dc.identifier.urihttps://shareok.org/handle/11244/336578
dc.languageen_USen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectmulti-goal problemsen_US
dc.subjectcompromise decision support problemsen_US
dc.subjectadaptive leveling-weighting-clustering (ALWC) methoden_US
dc.subjectclustering analysisen_US
dc.titleManaging multi-goal design problems using adaptive leveling-weighting-clustering algorithmen_US
dc.typeArticleen_US
ou.groupGallogly College of Engineering::School of Industrial and Systems Engineeringen_US

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