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Product Optimization Incorporating Discrete Design Variables Based on Decomposition of Performance Characteristics

[+] Author Affiliations
Masataka Yoshimura, Yu Yoshimura, Kazuhiro Izui, Shinji Nishiwaki

Kyoto University, Kyoto, Japan

Paper No. DETC2006-99187, pp. 711-720; 10 pages
  • ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1: 32nd Design Automation Conference, Parts A and B
  • Philadelphia, Pennsylvania, USA, September 10–13, 2006
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 0-7918-4255-X | eISBN: 0-7918-3784-X
  • Copyright © 2006 by ASME


In order to obtain superior design solutions, the largest possible number of design alternatives, often expressed as discrete design variables, should first of all be considered, and the best design solution should then be selected from this wide set of alternative designs. Also, product designs should be initiated from the earliest possible stages, such as the conceptual and fundamental design stages, when discrete rather than continuous design variables have primacy. Although the use of discrete design variables is fundamentally important, this has implications in terms of computational demands and the accuracy of the optimized solution. This paper proposes an optimization method for product designs incorporating discrete design variables, in which hierarchical product optimization methodologies are constructed based on decomposition of characteristics and/or extraction of simpler characteristics. The optimizations are started at the lowest levels of the hierarchical optimization structure, and proceed to the higher levels. The discrete design variables are efficiently selected and optimized as smaller sub-optimization problems at the lowest hierarchical levels, while the optimum solutions for the entire problem are obtained by conventional mathematical programming methods. Practical optimization procedures for machine product optimization problems having several types of discrete design variables are constructed, and some applied examples demonstrate their effectiveness.

Copyright © 2006 by ASME



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