Single Run Optimization of Discrete Event Simulations—An Empirical Study Using the M/M/l Queue

REFERENCES

• Azadivar , F. , J. Talavage , ( 1980 ) “ Optimization of Stochastic Simulation Models ,” Mathematics andCompuiers in Simulation 22 , 231 – 241 .
   Google Scholar
• Biles , W.E. , J.J. Swain , ( 1980 ). Optimization and Industrial Experimentation , John Wiley , New York .
   Google Scholar
• Blum , J.R. ( 1954a ). “ Approximation Methods which Converge with Probability One ,” Annals of Math. Stat . 25 , 382 – 386 .
   Google Scholar
• Blum , J.R. ( 1954b ), “ Multidimensional Stochastic Approximation Methods ,” Annals of Math. Stat . 25 , 721 – 144 .|bt
   Google Scholar
• Davits , O.L. (ed.). ( 1970 ). Design and Analysis of Industrial Experiments , Hafner , New York .
   Google Scholar
• Dvoretzky , A. ( 1956 ). “ On Stochastic Approximation ,” Proc. of 3rd Berkeley Symposium on Math. Stat, and Probability , 39 – 55 .
   Google Scholar
• Farell , W. ( 1977 ). “ Literature Review and Bibliography of Simula-tion Optimization ,” Proc. of.1977 Winter Simulation Conference , 117 – 124 ,
   Google Scholar
• Friedman , M. , L.J. , Savage , ( 1947 ). Ch. 13 in C. Eisenhart, M. Hastay, and W. Wallis (ed.) , Techniques of Statistical Analysis , McGraw-Hill , New York .
   Google Scholar
• Glynn , P.W. ( 1986a ). “ Optimization of Stochastic Systems ,” Proc. of 1986 Winter Simulation Conference|bt, 52 – 59 .
   Google Scholar
• Glynn , P.W. ( 1986b ). “ Stochastic Approximation for Monte Carlo Optimization ,” Proc. of 1986 Winter Simulation Conference , 356 – 365 .
   Google Scholar
• Ho , Y.C. ( 1985 ). “ A Survey of the Perturbati cm Analysis of Discrete Event Dynamic Systems ” Annals of Oper. Res. 3 , 393 – 402 .
   Google Scholar
• Ho , Y.C. , X. Cao , ( 1983 ). “ Perturbation Analysis and Optimization of Queueing Networks .” J. ofOptim. Theory and Applic . 40, 4 , 559 – 582 .
   Web of Science ®Google Scholar
• Ho , Y.C. , M.A. Eyler and T.T. Chien , ( 1979 ), “ A Gradient Technique for General Buffer Storage Design in a Serial Production Line ,” Int. J. of Prod. Res. 17, 6 , 557 – 580 .
   Web of Science ®Google Scholar
• Ho , Y.C. , M.A. Eyler , T.T. , Chieo . ( 1983 ). “ A New Approach to Determine Parameter Sensitivities of Transfer Lines ,” Monag. Set. 29, 6 , 700 – 714 .
   Web of Science ®Google Scholar
• Ho , Y.C. , R. Suri , X.R. Cao , G.W. Diehl , J.W. Dille , M.A. Zazanis . ( 1984 ). “ Optimization of Large Multiclass (Non-product Form) Queueing Networks Using Perturbation Analysis ,” large Scale Systems 7 , 165 – 180 .
   Google Scholar
• Hooke , R. , T.A. Jeeves . ( 1961 ). “ A Direct Search Solution of Numerical and Statistical Problems ,” J of ACM 8 , 2 , 212 – 229 .
   Google Scholar
• Kesten , H. ( 1958 ). “ Accelerated Stochastic Approximation ,” Annals of Math. Stat . 29 , 41 – 59 .
   Google Scholar
• Kiefer . J.J. Wolfowitz . ( 1952 ). “ Stochastic Estimation of the Maximum of a Regression Function ,” Annals of Math. Slat . 23 , 462 – 466 .
   Google Scholar
• Law , A.M. ,JS. Carson. ( 1979 ). “ A Sequential Procedure for Detenruning the Length of a Steady-State Simulation ,” Oper. Res. 27 , 1011 – 1025 .
   Web of Science ®Google Scholar
• Meketon , M.S. ( 1983 ). “ A Tutorial on Optimization in Simulations ,“ presented at the 1983 Winter Simulation Conference .
   Google Scholar
• Meketon , M.S. and P. Heidelberger . ( 1982 ). “ A Renewal Theoretic Approach to Bias Reduction in Regenerative Simulations ,” Manag. Sci. 28 , 2 , 173 – 181 .
   Web of Science ®Google Scholar
• Robbias , H. and S. Monro . ( 1951 ). “ A Stochastic Approximation Method ,” Annals of Math. Stat . 22 , 400 – 407 .
   Google Scholar
• Sacks , J. , ( 1958 ). “ Asymptotic Distribution of Stochastic Approximation Procedures ,” Annals of Math. Sun. , 29 , 373 – 405 .
   Google Scholar
• Smith , D.E. ( 1973 ). “ An Empirical Investigation of Optimum-Seeking in the Computer Simulation Situation ,” Oper. Res , 21, 2 , 475497 .
   Web of Science ®Google Scholar
• Suri , R. ( 1987 ). “ Infinitesimal Perturbation Analysis for General Discrete Event Systems .” J. of ACM 34. 3 , 686 – 717 .
   Web of Science ®Google Scholar
• Suri , R. and J.W. Dille . ( 1985 ). “ A Techniqe forOo-LirteSensitivi- ty Analysis of Flexible ManufacturingSystems ,” Annals of Oper. Res , 3 , 381 – 392 .
   Google Scholar
• Sun , R. and M.A. Zazanis . ( 1988 ). “ Perturbation Analysis Gives Strongly Consistent Sensitivity Estimates for the M/G/l Queue ,” Manag. Sci. 34 , 1 , 39 – 64 .
   Web of Science ®Google Scholar
• Taha , HA. ( 1976 ). Operations Research An Introduction , 2nd ed. , Macmillan , New York , Ch. 13 .
   Google Scholar
• Zazanis , M.A. and R. , Suri . ( 1985 ). “ Estimating Second Derivatives of Performance Measures for 0/6/1 Queues from a Single Sample Path .” working paper, Division of Applied Sciences , Harvard University , Cambridge , MA .
   Google Scholar