Applying Response Surface Approximation for Engineering Optimization with Fuzzy Parameters and Fuzzy Variables

碩士 === 淡江大學 === 機械與機電工程學系碩士班 === 95 === A design optimization problem contains fuzzy information such as fuzzy parameters and variable is often confronted in engineering applications. Particularly in the modern engineering problems, finite element method is popular used for the analysis in various...

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Bibliographic Details
Main Authors: Wen-Hsiang Chen, 陳文祥
Other Authors: Chieh-Jong Shih
Format: Others
Language:zh-TW
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/66916544357726532692
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Summary:碩士 === 淡江大學 === 機械與機電工程學系碩士班 === 95 === A design optimization problem contains fuzzy information such as fuzzy parameters and variable is often confronted in engineering applications. Particularly in the modern engineering problems, finite element method is popular used for the analysis in various engineering optimization problems with fuzzy information. This thesis presents the study of finite-element based engineering design optimization containing fuzzy parameters and fuzzy design variables; and the crisp design variables contain a mix of real continuous variables and discrete variables. For dealing with such kind of problem, the optimization with approximation technique of applying the response surface method is developed and presented in this thesis. The simple first-order response surface approximation with suitable sequential searching technique including confidence move limit technique has been used for locating the optimum. There are three critical sides considerably influence the result. The first one is how to deal with the fuzzy optimization problem containing fuzzy information existing in design variables and parameters so that a crisp optimization can be solved. Because of the fuzzy region of each fuzzy variable is vary, it is required to consider a way of design control so that the performance robustness can be achieved. The second one is how to deal with the discrete variables in the approximation environment constructed by response surface function. The third one is how to perform the optimization searching process to obtain the optimum result. For applying the proposed design methodology to the two-objective problem, the important point is how to define and select the ideal solution corresponding to individual objective during the whole optimization searching process. All above three considerations are presented in the thesis. One ten-bar truss with finite element analysis optimization problem is adopted in the thesis as a model for proposed development and demonstrating the presented concept, process and application.