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Optimization and sensitivity analysis of computer simulation models by the score function method. (English) Zbl 0911.90166

Summary: This paper surveys some recent results on the score function (SF) method. This method is suitable for performance evaluation, sensitivity analysis, and optimization of complex discrete-event systems such as non-Markovian queueing systems.

MSC:

90B22 Queues and service in operations research
65C20 Probabilistic models, generic numerical methods in probability and statistics

References:

[1] Aleksandrov, V. M.; Sysoyev, V. I.; Shemeneva, V. V., Stochastic Optimization, Engineering Cybernetics, 5, 11-16 (1968)
[2] Asmussen, S., Applied Probability and Queues (1987), Wiley: Wiley New York · Zbl 0624.60098
[3] Ermakov, C. M.; Mikhailov, G. A., Statistical Modeling (1982), Nauka: Nauka Moscow, (in Russian) · Zbl 0599.65001
[4] Feuerverger, A.; McLeish, D. L.; Rubinstein, R. Y., A cross-spectral method for sensitivity analysis of computer simulation models, (Comptes Rendus: Mathematical Reports of the Academy of Sciences, VIII (1986), Royal Society of Canada), 335-339, 5
[5] Fu, C. M., Optimization in simulation: A review, Annals of Operations Research, 53, 199-247 (1994) · Zbl 0833.90089
[6] Glasserman, P., Gradient Estimation via Perturbation Analysis (1991), Kluwer: Kluwer Norwell, MA · Zbl 0746.90024
[7] Glynn, P. W., Likelihood ratio gradient estimation for stochastic systems, Communications of the ACM, 33, 10, 75-84 (1990)
[8] Gross, D.; Harris, C., Fundamentals of Queueing Theory (1985), Wiley: Wiley New York · Zbl 0658.60122
[9] Ho, Y. C.; Cao, X. R., Perturbation Analysis of Discrete Event Systems (1991), Kluwer: Kluwer Boston, MA · Zbl 0595.60087
[10] Itzhaki, Ya., Stochastic optimization of open queueing networks by the score function method, (Master’s Thesis (1994), Technion: Technion Haifa, Israel)
[11] Kleijnen, J. P.C., Statistical Tools for Simulation Practitioners (1987), Marcel Dekker: Marcel Dekker New York · Zbl 0629.62004
[12] Kleijnen, J. P.C., Sensitivity analysis and optimization of simulation models, (Proceedings of the 1994 European Simulation Symposium (1994), The Society for Computer Simulation: The Society for Computer Simulation California) · Zbl 0731.90001
[13] Kreimer, J., Stochastic optimization — An adaptive approach, (D.Sc. Thesis (1984), Technion: Technion Haifa, Israel) · Zbl 0657.93059
[14] Kriman, V., Sensitivity analysis of \(GI / GI /m/B\) queues with respect to buffer size by the score function method, Stochastic Models (1994), to appear
[15] L’Ecuyer, P. L., A unified version of the IPA, SF, and LR gradient estimation techniques, Management Science, 36, 11, 1364-1383 (1990) · Zbl 0731.65130
[16] Marti, K., Stochastic optimization methods of structural design, Zeitschrift für Angewandte Mathematik und Mechanik, 4, T742-T745 (1990) · Zbl 0719.73033
[17] Mikhailov, G. A., Calculation of system parameter derivatives of functionals of the solutions to the transport equations, Zhurnal Vychislitel’noi Matematiki i Matematicheskoi Fiziki, 7, 915 (1967)
[18] Miller, L. B., Monte Carlo analysis of reactivity coefficients in fast reactors: general theory and applications, (ANL-7307 (TID-4500) (1967), Argonne National Laboratory: Argonne National Laboratory IL)
[19] Reiman, M. I.; Weiss, A., Sensitivity analysis for simulations via likelihood ratios, Operations Research, 37, 5, 830-844 (1989) · Zbl 0679.62087
[20] Rubinstein, R. Y., Some problems in Monte Carlo optimization, (PhD Thesis (1969), Riga: Riga Latvia) · Zbl 0506.90061
[21] Rubinstein, R. Y., Monte Carlo Optimization Simulation and Sensitivity of Queueing Network (1986), Wiley: Wiley New York · Zbl 0664.65059
[22] Rubinstein, R. Y., Sensitivity analysis of discrete event systems by the “Push out” method, Annals of Operations Research, 39, 229-251 (1992) · Zbl 0776.93024
[23] Rubinstein, R. Y.; Kreimer, J., About one Monte Carlo method for solving linear equations, Mathematics and Computers in Simulation, XXV, 321-334 (1983) · Zbl 0545.65026
[24] Rubinstein, R. Y.; Shapiro, A., Discrete Event Systems: Sensitivity Analysis and Stochastic Optimization via the Score Function Method (1993), Wiley: Wiley New York · Zbl 0805.93002
[25] Uryas’ev, S., Analytic perturbation analysis for DEDS with discontinuous sample-path functions, (Manuscript (1994), Brookhaven National Laboratory: Brookhaven National Laboratory Upton, NY)
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