Journal of the Korean Society for Railway (한국철도학회논문집)

The Korean Society for Railway (한국철도학회)
권호 표지

The Optimal Design Method of the Train Repair Facility based on the Simulation

시뮬레이션을 이용한 철도 정비 시설의 최적 설계 방법

  • 엄인섭 (고려대학교 정보경영공학부) ;
  • 천현재 (고려대학교 BK21 유비쿼터스 정보보호사업단) ;
  • 이홍철 (고려대학교 정보경영공학부)
  • Published : 2007.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

This paper presents the optimal design method of the train repair facility based on the simulation analysis. The train is divided into the power car, motorized car and passenger car for the simulation process analysis and train repair facility is composed of each subsystems such as a blast, dry and wash workshop. In simulation analysis, we consider the critical (dependent) factors and design (independent) factors for the optimal design. Therefore, a simulation optimization uses Evolution Strategy (ES) in order to find the optimal design factors. Experimental results indicate that simulation design factors are sufficient to satisfy the conditions of dependent variables. The proposed analysis method demonstrates that simulation design factors determined by the simulation optimization are appropriate for real design factors in a real situation and the accuracy and confidence for the simulation results are increased.

Keywords

References

  1. 강정윤, 이홍철, 엄인섭 (2006), '시뮬레이션과 메타모델을 이용한 자동 물류 센터 설계 최적화', 한국 시뮬레이션 학회지, 제15권, 제5호, pp.103-114
  2. 엄인섭, 이홍철, 강정윤 (2004), '진화전략과 DEA를 이용한 통합 물류 시스템 분석 방법', 한국 시뮬레이션 학회지, 제13권, 제4호, pp.17-29
  3. 이상설, 안도만, 강희정(1999), '철도차량 정비공장의 설비배치 개선에 관한 연구', 공업 경영 학회지, 제22권, 제49호, 공업 경영학회, pp.89-98
  4. Brooks Automation, Inc. AutoSimulation Division (2001), 'AutoMod User's Manual', Brooks Automation, Inc
  5. Dewsnup, M. C. (1995), 'How to model AGVS using Promodel for Windows', Proceeding of 1995 Winter Simulation Conference, pp.703-708
  6. Jayaraman, A. (1993), 'Use of simulation-animation techniques in the design of an AGV system. M. Sc. Thesis', Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University
  7. King, R.E. and Kim, K.S. (1995), 'AgvTalk：An objectiveoriented simulator for AGV system', Computer and Industrial Engineering, Vol.28, No, 3, pp.575-592 https://doi.org/10.1016/0360-8352(94)00210-E
  8. Lee, J. (1996), 'Composite dispatching rules for multiple-vehicle AGV systems', Simulation, Vol. 66, No 2, pp.121-130 https://doi.org/10.1177/003754979606600208
  9. Moriarty, D. E., Schultz, A. C. and Grefenstette, J. J. (1999), 'Evolutionary Algorithms for Reinforcement Learning', Journal of Artificial Intelligence Research, Vol. 11, pp.241-276 https://doi.org/10.1613/jair.613
  10. Michalewicz, Z. (1996), 'Genetic Algorithms + Data Structures =Evolution Programs 3rd Edition', Springer-Verlag
  11. Schwefel, H. P. (1991), 'Evolution and Optimum Seeking', NewYork, John Wiley & Sons
  12. Tanchoco, J. M. A. (1994), 'Material Flow system in Manufacturing', Chapman & Hall