NDLI: GA-Based Multi-Objective Fuzzy Matter-Element Optimization

Content Provider	The American Society of Mechanical Engineers (ASME) Digital Collection
Author	Zhao, Yanwei Hua, Ertian Zhang, Guoxian Jin, Fangshun
Abstract	The solving strategy of GA-Based Multi-objective Fuzzy Matter-Element optimization is put forward in this paper to the kind of characters of product optimization such as multi-objective, fuzzy nature, indeterminacy, etc. Firstly, the model of multi-objective fuzzy matter-element optimization is created in this paper, and then it defines the matter-element weightily and changes solving multi-objective optimization into solving dependent function K(x) of the single objective optimization according to the optimization criterion. In addition, modified adaptive macro genetic algorithms (MAMGA) are adopted to solve the optimization problem. It emphatically modifies crossover and mutation operator. By the comparing MAMGA with adaptive macro genetic algorithms (AMGA), not only the optimization is a little better than the latter, but also it reaches the extent to which the effective iteration generation is 62.2% of simple genetic algorithms (SGA). Lastly, three optimization methods, namely fuzzy matter-element optimization, linearity weighted method and fuzzy optimization, are also compared. It certifies that this method is feasible and valid.
Sponsorship	Design Engineering Division and Computers and Information in Engineering Division
Starting Page	663
Ending Page	669
Page Count	7
File Format	PDF
ISBN	0791836223
DOI	10.1115/DETC2002/DAC-34104
e-ISBN	0791836037
Volume Number	Volume 2: 28th Design Automation Conference
Conference Proceedings	ASME 2002 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
Language	English
Publisher Date	2002-09-29
Publisher Place	Montreal, Quebec, Canada
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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