Preference set-based design method for qualitative assessments using dominance-based rough set approach

The preference set-based design (PSD) method enhances design efficiency by providing an adjustment range that reflects the preferences of the designer in the quantitative design variables and performance. However, applying PSD in early design stages, where variables and performance are often qualita...

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Main Authors: Shotaro OYAMA, Takeo KATO
Format: Article
Language:English
Published: The Japan Society of Mechanical Engineers 2025-04-01
Series:Journal of Advanced Mechanical Design, Systems, and Manufacturing
Subjects:
Online Access:https://www.jstage.jst.go.jp/article/jamdsm/19/2/19_2025jamdsm0018/_pdf/-char/en
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author Shotaro OYAMA
Takeo KATO
author_facet Shotaro OYAMA
Takeo KATO
author_sort Shotaro OYAMA
collection DOAJ
description The preference set-based design (PSD) method enhances design efficiency by providing an adjustment range that reflects the preferences of the designer in the quantitative design variables and performance. However, applying PSD in early design stages, where variables and performance are often qualitative or their relationships fluctuate probabilistically owing to individual differences (probabilistic objective function), is challenging. This study proposes a PSD method that addresses these issues using the rough set theory, which is suitable for handling such design problems. This approach derives if-then rules from data combining qualitative and quantitative design variables and performance. These rules are specified based on four PSD indicators and target either frequently occurring or high-importance data. The proposed method was validated on car evaluation data from a U.S. automobile market. The analysis resulted in decision rules incorporating both quantitative and qualitative design variables, as well as the characteristics of four indicators. This demonstrates the applicability of the proposed method to design problems with qualitative variables and performance or a probabilistic objective function. Additionally, a parameter study of indicator weights yielded diverse decision rules (Pareto optimal solutions) based on the weight ratio, highlighting the ability of the proposed method to generate design solutions aligned with specific characteristics of each indicator, further confirming its applicability to a wide range of design problems.
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publisher The Japan Society of Mechanical Engineers
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spelling doaj-art-f5a37dac5f3049ada7fa6c0b00a771602025-08-20T02:43:28ZengThe Japan Society of Mechanical EngineersJournal of Advanced Mechanical Design, Systems, and Manufacturing1881-30542025-04-01192JAMDSM0018JAMDSM001810.1299/jamdsm.2025jamdsm0018jamdsmPreference set-based design method for qualitative assessments using dominance-based rough set approachShotaro OYAMA0Takeo KATO1School of Integrated Design Engineering, Keio UniversityDepartment of Mechanical Engineering, Keio UniversityThe preference set-based design (PSD) method enhances design efficiency by providing an adjustment range that reflects the preferences of the designer in the quantitative design variables and performance. However, applying PSD in early design stages, where variables and performance are often qualitative or their relationships fluctuate probabilistically owing to individual differences (probabilistic objective function), is challenging. This study proposes a PSD method that addresses these issues using the rough set theory, which is suitable for handling such design problems. This approach derives if-then rules from data combining qualitative and quantitative design variables and performance. These rules are specified based on four PSD indicators and target either frequently occurring or high-importance data. The proposed method was validated on car evaluation data from a U.S. automobile market. The analysis resulted in decision rules incorporating both quantitative and qualitative design variables, as well as the characteristics of four indicators. This demonstrates the applicability of the proposed method to design problems with qualitative variables and performance or a probabilistic objective function. Additionally, a parameter study of indicator weights yielded diverse decision rules (Pareto optimal solutions) based on the weight ratio, highlighting the ability of the proposed method to generate design solutions aligned with specific characteristics of each indicator, further confirming its applicability to a wide range of design problems.https://www.jstage.jst.go.jp/article/jamdsm/19/2/19_2025jamdsm0018/_pdf/-char/enset-based designrough set theorydesign methodologyconcurrent engineeringdesign preference
spellingShingle Shotaro OYAMA
Takeo KATO
Preference set-based design method for qualitative assessments using dominance-based rough set approach
Journal of Advanced Mechanical Design, Systems, and Manufacturing
set-based design
rough set theory
design methodology
concurrent engineering
design preference
title Preference set-based design method for qualitative assessments using dominance-based rough set approach
title_full Preference set-based design method for qualitative assessments using dominance-based rough set approach
title_fullStr Preference set-based design method for qualitative assessments using dominance-based rough set approach
title_full_unstemmed Preference set-based design method for qualitative assessments using dominance-based rough set approach
title_short Preference set-based design method for qualitative assessments using dominance-based rough set approach
title_sort preference set based design method for qualitative assessments using dominance based rough set approach
topic set-based design
rough set theory
design methodology
concurrent engineering
design preference
url https://www.jstage.jst.go.jp/article/jamdsm/19/2/19_2025jamdsm0018/_pdf/-char/en
work_keys_str_mv AT shotarooyama preferencesetbaseddesignmethodforqualitativeassessmentsusingdominancebasedroughsetapproach
AT takeokato preferencesetbaseddesignmethodforqualitativeassessmentsusingdominancebasedroughsetapproach