Applications of Micro Genetic Algorithms to Engineering Design Optimization

마이크로 유전알고리듬의 최적설계 응용에 관한 연구

  • 김종헌 (연세대학교 대학원 기계공학과) ;
  • 이종수 (연세대학교 기계공학부) ;
  • 이형주 (한국시뮬레이션기술(주)) ;
  • 구본흥 ((주)브이엠테크)
  • Published : 2003.01.01


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.


Evolutionary Computing;Micro-Genetic Algorithms;Structural Optimization;Injection Molding


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