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http://dx.doi.org/10.3795/KSME-A.2003.27.1.158

Applications of Micro Genetic Algorithms to Engineering Design Optimization  

Kim, Jong-Hun (연세대학교 대학원 기계공학과)
Lee, Jong-Soo (연세대학교 기계공학부)
Lee, Hyung-Joo (한국시뮬레이션기술(주))
Koo, Bon-Heung ((주)브이엠테크)
Publication Information
Transactions of the Korean Society of Mechanical Engineers A / v.27, no.1, 2003 , pp. 158-166 More about this Journal
Abstract
The paper describes the development and application of advanced evolutionary computing techniques referred to as micro genetic algorithms ($\mu$GA) in the context of engineering design optimization. The basic concept behind $\mu$GA draws from the use of small size of population irrespective of the bit string length in the representation of design variable. Such strategies also demonstrate the faster convergence capability and more savings in computational resource requirements than simple genetic algorithms (SGA). The paper first explores ten-bar truss design problems to see the optimization performance between $\mu$GA and SGA. Subsequently, $\mu$GA is applied to a realistic engineering design problem in the injection molding process optimization.
Keywords
Evolutionary Computing; Micro-Genetic Algorithms; Structural Optimization; Injection Molding;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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