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다측면 유전자 알고리즘을 이용한 시뮬레이션 최적화 기법
A Simulation Optimization Method Using the Multiple Aspects-based Genetic Algorithm

박성진    (고려대학교 전산학과 소프트웨어시스템 연구실  );
  • 초록

    For many optimization problems where some of the system components are stochastic, the objective functions cannot be represented analytically. Therefore, modeling by computer simulation is one of the most effective means of studying such complex systems. Many, if not most, simulation optimization problems have multiple aspects. Historically, multiple aspects have been combined ad hoc to form a scalar objective function, usually through a linear combination (weighted sum) of the multiple attributes, or by turning objectives into constraints. The genetic algorithm (GA), however, is readily modified to deal with multiple aspects. In this paper we propose a MAGA (Multiple Aspects-based Genetic Algorithm) as an algorithm for finding the Pareto optimal set. We demonstrate its ability to find and maintain a diverse "Pareto optimal population" on two problems.


  • 참고문헌 (14)

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