التفاصيل البيبلوغرافية
| العنوان: |
Optimal Engineering System Design Guided by Data-Mining Methods. |
| المؤلفون: |
Pansoo Kim1 pskim@knu.ac.kr, Yu Ding2 yuding@iemail.tamu.edu |
| المصدر: |
Technometrics. Aug2005, Vol. 47 Issue 3, p336-348. 13p. |
| مصطلحات موضوعية: |
*ENGINEERING design, *INDUSTRIAL design, *DATA mining, *DATABASE searching, *DATABASE marketing, COMBINATORIAL optimization |
| مستخلص: |
An optimal engineering design problem is challenging because nonlinear objective functions usually need to be evaluated in a high-dimensional design space. This article presents a data-mining-aided optimal design method, that is able to find a competitive design solution with a relatively low computational cost. The method consists of four components: (1) a uniform-coverage selection method, that chooses design representatives from among a large number of original design alternatives for a nonrectangular design space; (2) feature functions, of which evaluation is computationally economical as the surrogate for the design objective function; (3) a clustering method, that generates a design library based on the evaluation of feature functions instead of an objective function; and (4) a classification method to create the design selection rules, eventually leading us to a competitive design. Those components are implemented to facilitate the optimal fixture layout design in a multistation panel assembly process. The benefit of the data-mining-aided optimal design is clearly demonstrated by comparison with both local optimization methods (e.g., simplex search) and random search-based optimizations (e.g., simulated annealing). [ABSTRACT FROM AUTHOR] |
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