Response gradient estimation using mathematical programming models of discrete-event system sample paths

Proceedings - Winter Simulation Conference

Volumn , Issue , 2006, Pages 272-278

  Chan, Wai Kin ^a   Schruben, Lee W ^b  

^a RENSSELAER POLYTECHNIC INSTITUTE   (United States)

^b DEPARTMENT OF INDUSTRIAL ENGINEERING AND OPERATIONS RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BLIND SOURCE SEPARATION; FINITE DIFFERENCE METHOD; GRADIENT METHODS; LINEAR PROGRAMMING; LINEARIZATION; MATHEMATICAL MODELS; MATHEMATICAL PROGRAMMING; URBAN PLANNING;

DISCRETE-EVENT SYSTEM (DES); FINITE DIFFERENCE (FD); GRADIENT ESTIMATES; GRADIENT ESTIMATION; GRADIENT ESTIMATOR; MATHEMATICAL PROGRAMMING MODELS; PROPERTY (S); SAMPLE PATHS; TOLERANCE LIMITS;

ESTIMATION;

EID: 46149125559     PISSN: 08917736     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WSC.2006.323083     Document Type: Conference Paper

References (19)

1. Cao, X. R. (1985). Convergence of parameter sensitivity estimates in a stochastic experiment. IEEE Transactions on Automatic Control 30(9): 845-853.
2. Cao, X. R. and H.-F. Chen (1997). Perturbation realization, potentials, and sensitivity analysis of Markov processes. Automatic Control, IEEE Transactions on 42(10): 1382-1393.
3. Chan, W. K. V. (2005). Mathematical Representations of Discrete-Event System Dynamics. Ph.D. dissertation, University of California, Berkeley.
4. Chan, W. K. V. and L. W. Schruben (2003). Properties of discrete event systems from their mathematical programming representations. Proceedings of the 2003 Winter Simulation Conference (IEEE Cat. No. 03CH7499), ed. Chick, S. E., Sanchez, P. J., Ferrin, D., and Morrice, D. J., IEEE. Part Vol. 1, 2003, pp.496-502 Vol. 1. Piscataway, NJ, USA.
5. Freimer, M. and L. Schruben (2001). Graphical representation of IPA estimation. Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304), ed. Peters, B. A., Smith, J. S., Medeiros, D. J., Rohrer, M. W., IEEE. Part Vol. 1, 2001, pp.422-7 vol. 1. Piscataway, NJ, USA.
6. Fu, M. and J.-Q. Hu (1997). Conditional Monte Carlo : gradient estimation and optimization applications, Kluwer Academic Publishers, Boston.
7. Fu, M. C. and J. Q. Hu (1991). Consistency of infinitesimal perturbation analysis for the GI/G/m queue. European Journal of Operational Research 54(1): 121-39.
8. Gal, T. (1979). Postoptimal Analyses, Parametric Programming and Related Topics, McGraw-Hill, London.
9. Glasserman, P. (1991a). Gradient Estimation via Perturbation Analysis, Kluwer Academic Publishers, Boston.
10. Glasserman, P. (1991b). Structural conditions for perturbation analysis of queuing-systems. Journal of the Association for Computing Machinery 38(4): 1005-1025.
11. Gong, W. B. and Y. C. Ho (1987). Smoothed (conditional) perturbation analysis of discrete event dynamic-systems. Ieee Transactions on Automatic Control 32(10): 858-866.
12. Ho, Y. C. and X. Cao (1991). Perturbation Analysis of Discrete Event Dynamic Systems, Kluwer Academic Publishers, Boston.
13. Ho, Y. C., M. A. Eyler and T. T. Chien (1979). A gradient technique for general buffer storage design in a production line. International Journal of Production Research 17(6): 557-580.
14. Homem-de-Mello, T., A. Shapiro and M. L. Spearman (1999). Finding optimal material release times using simulation-based optimization. Management Science 45(1): 86-102.
15. Lindley, D. V. (1952). The theory of queues with a single server. Proceedings of the Cambridge Philosophical Society 48(2): 277-289.
16. Schruben, L. W. (2000). Mathematical programming models of discrete event system dynamics. 2000 Winter Simulation Conference Proceedings (Cat. No. 00CH37165), ed. Joines, J. A., Barton, R. R., Kang, K., and Fishwick, P. A., IEEE. Part vol.1, 2000, pp.381-5 vol.1. Piscataway, NJ, USA.
17. Suri, R. (1987). Infinitesimal perturbation analysis for general discrete event systems. Journal of the ACM 34(3): 686-717.
18. Suri, R. (1989). Perturbation analysis - the state of the art and research issues explained Via the GI/G/1 Queue. Proceedings of the IEEE 77(1): 114-137.
19. Suri, R. and M. A. Zazanis (1988). Perturbation analysis gives strongly consistent sensitivity estimates for the M/G/1 queue. Management Science 34(1): 39-64.