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.
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M3 - Conference contribution
AN - SCOPUS:34147176081
SN - 1563478080
SN - 9781563478086
T3 - Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
SP - 5479
EP - 5522
BT - Collection of Technical Papers - 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
T2 - 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference
Y2 - 1 May 2006 through 4 May 2006
ER -