TY - JOUR
T1 - A Study on Structural Optimum Design Based on Qualitative Sensitivities
AU - Arakawa, Masao
AU - Yamakawa, Hiroshi
PY - 1993
Y1 - 1993
N2 - An optimum design method is considered as a method whose results are the most reasonable from various standpoints in the prescribed mathematical formulation. However, its formulations present difficulities in choosing objective functions, setting allowances to constraints and so on, because they are greatly concerned with the results of optimization. In this study, we proposed concepts of qualitative sensitivities and qualitative optimality compared to quantitative concepts, and proposed a general algorithm of the qualitive optimization method. We newly defined three kinds of fuzzy language and assigned fuzzy sets to each of them and assigned them to each candidate of discrete design variable. We propose fuzzy reasoning rules by using these two kinds of fuzzy sets. We also extend the proposed algorithm to multiobjective optimization. Through the numerical example of a single objective problem, we obtained almost the same solution as in quantitative methods, and efficiencies were confirmed for this case. Also through the example to multiobjective problem, the new method was shown to have more flexibility in deciding in deciding the preferred objective functions compared to the conventional method.
AB - An optimum design method is considered as a method whose results are the most reasonable from various standpoints in the prescribed mathematical formulation. However, its formulations present difficulities in choosing objective functions, setting allowances to constraints and so on, because they are greatly concerned with the results of optimization. In this study, we proposed concepts of qualitative sensitivities and qualitative optimality compared to quantitative concepts, and proposed a general algorithm of the qualitive optimization method. We newly defined three kinds of fuzzy language and assigned fuzzy sets to each of them and assigned them to each candidate of discrete design variable. We propose fuzzy reasoning rules by using these two kinds of fuzzy sets. We also extend the proposed algorithm to multiobjective optimization. Through the numerical example of a single objective problem, we obtained almost the same solution as in quantitative methods, and efficiencies were confirmed for this case. Also through the example to multiobjective problem, the new method was shown to have more flexibility in deciding in deciding the preferred objective functions compared to the conventional method.
KW - Design Engineering
KW - Fuzzy Reasoning
KW - Fuzzy Set Theory
KW - Optimum Design
KW - Qualitative Sensitivity
KW - Sensitivity Analysis
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U2 - 10.1299/kikaic.59.422
DO - 10.1299/kikaic.59.422
M3 - Article
AN - SCOPUS:84998259270
SN - 0387-5024
VL - 59
SP - 422
EP - 429
JO - Transactions of the Japan Society of Mechanical Engineers Series C
JF - Transactions of the Japan Society of Mechanical Engineers Series C
IS - 558
ER -