Journal of the Korea Society for Simulation (한국시뮬레이션학회논문지)

The Korea Society for Simulation (한국시뮬레이션학회)
권호 표지

A Simulation Optimization Method Using the Multiple Aspects-based Genetic Algorithm

다측면 유전자 알고리즘을 이용한 시뮬레이션 최적화 기법

  • 박성진 (고려대학교 전산학과 소프트웨어시스템 연구실)
  • Published : 1997.06.01
Download PDF
⟨ Previous Next ⟩

Abstract

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.

Keywords

References

  1. 한국시뮬레이션학회 논문지 v.3 no.2 시뮬레이션 최적화 기법과 절삭 공정에의 응용 양병희;이영해
  2. Proceedings of the Fifth International Conference on Genetic Algorithms Genetic algorithms for multiobjective optimization: formulation, discussion and generalization C.M. Fonseca;P.J. Fleming
  3. Genetic Algorithms in Search, Optimization, and Machine Learning D.E. Goldberg
  4. Genetic Algorithms and Their Applications: Proceedings of the Second ICGA Genetic algorithms with sharing for multimodal function optimization D.E. Goldberg;J.J. Richardson
  5. Proceedings of the 1992 Winter Simulation Conference A Tutorial in Simulation Optimization F. Azadivar
  6. Proceedings of an International Conference on Genetic Algorithms and their Applications Multiple objective optimization with vector evaluated genetic algorithms J.D. Schaffer;J. Grefenstette(ed.)
  7. Proceedings of the First IEEE Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence v.1 A niched pareto genetic algorithm for multiobjective optimization J. Horn;N. Nafpliotis;D.E. Goldberg
  8. IlliGAL Report No. 93005, Illinois Genetic Algorithms Laboratory Multiobjective optimization using the niched Pareto genetic algorithm J. Horn;N. Nafpliotis
  9. Proceedings of the Third International Conference on Genetic Algorithms Some guidelines for genetic algorithms with penalty function J.T. Richardson;M.R. Liepins;M. Hilliard
  10. Naval Research Logistics v.37 Optimization in Simulation: Current Issues and the Future Outlook M.H. Safizadeh
  11. Proceedings of SCSC'95 Simulation and Optimization of Complex technical systems M. Syrjakow;H. Szczerbicka
  12. Proceedings of 1987 Winter Simulation Conference Optimization in Simulation : A Survey of Recent Results M.S. Meketon
  13. Proceedings of the SCSC'95 A simulation approach to data partitioning for distributed database design S.J. Park;J.P. Roh;D.K. Baik
  14. IEEE Trans. on Reliability v.41 no.1 Terminal-Pair Reliability of Tree-Type Computer Communication Networks W.W. Yang