Abstract
Although much attention has been focused on the development and applications of fuzzy optimization, multiobjective programming and mixed-discrete optimization methods separately, fuzzy multiobjective optimization problems in mixed-discrete design space were not addressed in the literature. It is mainly due to the lack of mature and robust theories of mixed-discrete and multiobjective optimization. In most practical applications, designers often encounter problems involving imprecise or fuzzy information, multiple objectives and mixed-discrete design variables. This paper presents a new method in which the fuzzy μ-formulation and game theory techniques are combined with a mixed-discrete hybrid genetic algorithm for solving mixed-dixcrete fuzzy multiobjective programming problems. Three example problems, dealing with the optimal designs of a two-bar truss, a conical convective spine and a twenty-five bar truss, demonstrate that the method can be flexibly and effectively applied to various kinds of engineering design problems to obtain more realistic and satisfactory results in an imprecise environment.
| Original language | English |
|---|---|
| Title of host publication | Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference |
| Pages | 5479-5522 |
| Number of pages | 44 |
| Volume | 8 |
| State | Published - Dec 1 2006 |
| Event | 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference - Newport, RI, United States Duration: May 1 2006 → May 4 2006 |
Other
| Other | 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference |
|---|---|
| Country | United States |
| City | Newport, RI |
| Period | 5/1/06 → 5/4/06 |
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ASJC Scopus subject areas
- Architecture
Cite this
Mixed-discrete fuzzy multiobjective optimization of fuzzy systems. / Rao, Singiresu S; Xiong, Ying.
Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. Vol. 8 2006. p. 5479-5522.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Mixed-discrete fuzzy multiobjective optimization of fuzzy systems
AU - Rao, Singiresu S
AU - Xiong, Ying
PY - 2006/12/1
Y1 - 2006/12/1
N2 - Although much attention has been focused on the development and applications of fuzzy optimization, multiobjective programming and mixed-discrete optimization methods separately, fuzzy multiobjective optimization problems in mixed-discrete design space were not addressed in the literature. It is mainly due to the lack of mature and robust theories of mixed-discrete and multiobjective optimization. In most practical applications, designers often encounter problems involving imprecise or fuzzy information, multiple objectives and mixed-discrete design variables. This paper presents a new method in which the fuzzy μ-formulation and game theory techniques are combined with a mixed-discrete hybrid genetic algorithm for solving mixed-dixcrete fuzzy multiobjective programming problems. Three example problems, dealing with the optimal designs of a two-bar truss, a conical convective spine and a twenty-five bar truss, demonstrate that the method can be flexibly and effectively applied to various kinds of engineering design problems to obtain more realistic and satisfactory results in an imprecise environment.
AB - Although much attention has been focused on the development and applications of fuzzy optimization, multiobjective programming and mixed-discrete optimization methods separately, fuzzy multiobjective optimization problems in mixed-discrete design space were not addressed in the literature. It is mainly due to the lack of mature and robust theories of mixed-discrete and multiobjective optimization. In most practical applications, designers often encounter problems involving imprecise or fuzzy information, multiple objectives and mixed-discrete design variables. This paper presents a new method in which the fuzzy μ-formulation and game theory techniques are combined with a mixed-discrete hybrid genetic algorithm for solving mixed-dixcrete fuzzy multiobjective programming problems. Three example problems, dealing with the optimal designs of a two-bar truss, a conical convective spine and a twenty-five bar truss, demonstrate that the method can be flexibly and effectively applied to various kinds of engineering design problems to obtain more realistic and satisfactory results in an imprecise environment.
UR - http://www.scopus.com/inward/record.url?scp=34147176081&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34147176081&partnerID=8YFLogxK
M3 - Conference contribution
SN - 1563478080
SN - 9781563478086
VL - 8
SP - 5479
EP - 5522
BT - Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
ER -