Abstract
In this paper we are concerned with the application of stochastic programming techniques for the parametric optimization and analysis of Discrete Events Dynamic Systems (DEDSs). In particular, we consider optimization of steady state behavior of DEDSs which sample path depends discontinuosly on control parameters.
This is a difficult problem, since in order to evaluate the steady state performance measure it is necessary to make an observation on the infinite time horizon, which is impossible. On the other hand, in the general case any observation on the finite time interval gives a biased estimates of the performance measure.
Here we consider an important subclass of DEDSs for which we developed a new algorithm for optimizing their steady state performance, by adapting the methods of stochastic optimization. Such subclass is the set of regenerative DEDSs.
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References
F. Archetti, A. Gaivoronski, A Sciomachen, Sensitivity Analysis and Optimization of Stochastic Petri Nets Journal of Discrete Event Dynamic Systems: Theory and Applications, vol. 3, pp. 5–37, 1993.
M. A. Crane, D. L. Iglehart, Simulating Stable Stochastic Systems. III Regenerative Processes and Discret Event Simulations, Oper. Research, vol. 23, pp. 33–45, 1975.
Yu Ermoliev, A. Gaivoronski, Stochastic Programming techniques for Optimisation for Discrete Event Systems Annals of Oper. Research 39, 1992.
Yu Ermoliev, R. J-B Wets, eds. Numerical Techniques for stochastic optimisation Springer Verlag, Berlin 1988.
A. Gaivoronski, L. Shi and R. Sreenivas Augmented Infinitesimal Perturbation Analysis: an Alternative Explanation Journal of DEDS 1992.
P.W. Glynn, Optimisation of Stochastic Systems in Proceedings of 1986 Winter Simulation Conference, 1986.
Y.C. Ho, Performance Evaluation and Perturbation Analysis of Discrete Event Dynamic Systems IEEE Transaction on Automatic Control, vol A.C. 32, No. 7, 1987, p 563–572.
Y. C. Ho, S. Li, Extentions of Infinitesimal Perturbation Analysis IEEE Transactions on Automatic Control, vol. AC-33, 1988, p. 427–438.
P. Kall Stochastic Linear Programming Springer Verlag, Berlin, 1976.
A. Prekopa Contribution to the Theory of Stochastic Programming Mathematical Programming 4, 202–221, 1973.
G. Ch. Pflug, Derivatives of Probability Measures — Concepts and Applications to the Optimisation of Stochastic Systems in Discrete Event Systems: Models and Applications, IIASA Conference, Sopron, Hungary, August 3–7, 1987; P. Varaja and A.B. Kurzhanski (eds.), Lecture Notes in Control and Information Sciences, Springer Verlag, 1988, p. 162–178.
R. Y. Rubistein. The Score Function Approach of Sensitivity Analysis of Computer Simulation Models. Math. and Computation in Simulations, vol 28, 1986, p. 351–379.
R. Suri, Infinitesimal Perturbation Analysis of General Discrete Event Systems, J. Assoc. Comput. Mach, 34, 1987, p 686–717.
R. J-B Wets, Stochastic Programming: Solution Techniques and Approximation Schemes in Mathematical Programming; The State of the Art 1982, A. Bachem, M. Groetschel and B. Korte (eds.), Springer Verlag, Berlin, 566–603.
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© 1994 Springer-Verlag
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Gaivoronski, A.A., Messina, E. (1994). Stochastic optimization algorithms for regenerative deds. In: Henry, J., Yvon, JP. (eds) System Modelling and Optimization. Lecture Notes in Control and Information Sciences, vol 197. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0035481
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DOI: https://doi.org/10.1007/BFb0035481
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