DocumentCode :
1985961
Title :
Application of the Modified Genetic Algorithm to Multi-response Robust Design Based on the Entropy Weight and the Desirability Function
Author :
Liuyang Zhang ; Yizhong Ma ; Linhan Ouyang ; Feng Wu
Author_Institution :
Sch. of Econ. & Manage., Nanjing Univ. of Sci. & Technol., Nanjing, China
Volume :
1
fYear :
2013
fDate :
28-29 Oct. 2013
Firstpage :
164
Lastpage :
168
Abstract :
How to consider the objective information of interesting responses in the course of new product design and development is discussed, when the subjective information cannot be accurately expressed by decision-makers. A modified desirability function approach is proposed to achieve robustness and optimization for multi-response optimization (MRO) problems. Because the modified desirability function is usually with multi-peak distribution, multi-constraints and high nonlinearity, the traditional gradient search algorithms are not suitable for searching the maxima of the function. So a modified genetic algorithm (MGA) is proposed to find optimal solutions. The example shows that the proposed method can obtain more effectively solutions for MRO problems.
Keywords :
entropy; genetic algorithms; product design; product development; MGA; MRO problems; desirability function; desirability function approach; entropy weight; modified genetic algorithm; multiconstraints; multipeak distribution; multiresponse optimization; multiresponse robust design; objective information; product design; product development; subjective information; Entropy; Genetic algorithms; Optimization; Product design; Robustness; Sociology; Statistics; MRO; desirability function; entropy weight; genetic algorithm; robust design;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design (ISCID), 2013 Sixth International Symposium on
Conference_Location :
Hangzhou
Type :
conf
DOI :
10.1109/ISCID.2013.48
Filename :
6804961
Link To Document :
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