A review of simulation optimization techniques

We present a review of methods for optimizing stochastic systems using simulation. The focus is on gradient based techniques for optimization with respect to continuous decision parameters and on random search methods for optimization with respect to discrete decision parameters.

[1]  J. Kiefer,et al.  Stochastic Estimation of the Maximum of a Regression Function , 1952 .

[2]  J. H. Venter.  An extension of the Robbins-Monro procedure , 1967 .

[3]  F. Downton.  Stochastic Approximation , 1969, Nature.

[4]  M. T. Wasan.  Stochastic Approximation , 1969 .

[5]  Carlos S. Kubrusly,et al.  Stochastic approximation algorithms and applications , 1973, CDC 1973.

[6]  Harold J. Kushner,et al.  wchastic. approximation methods for constrained and unconstrained systems , 1978 .

[7]  H. Robbins,et al.  Adaptive Design and Stochastic Approximation , 1979 .

[8]  Y. Ermoliev.  Stochastic quasigradient methods and their application to system optimization , 1983 .

[9]  D. Ruppert.  A Newton-Raphson Version of the Multivariate Robbins-Monro Procedure , 1985 .

[10]  Peter W. Glynn,et al.  Proceedings of Ihe 1986 Winter Simulation , 2022 .

[11]  H. Chen,et al.  STOCHASTIC APPROXIMATION PROCEDURES WITH RANDOMLY VARYING TRUNCATIONS , 1986 .

[12]  C. Z. Wei.  Multivariate Adaptive Stochastic Approximation , 1987 .

[13]  Akif Asil Bulgak,et al.  Integrating a modified simulated annealing algorithm with the simulation of a manufacturing system to optimize buffer sizes in automatic assembly systems , 1988, WSC '88.

[14]  D. Yan,et al.  Optimization algorithm with probabilistic estimation , 1988 .

[15]  S. Mitter,et al.  Simulated annealing with noisy or imprecise energy measurements , 1989 .

[16]  G. Yin,et al.  Almost sure convergence of stochastic approximation algorithms with non-additive noise , 1989 .

[17]  M. Fu.  Convergence of a stochastic approximation algorithm for the GI/G/1 queue using infinitesimal perturbation analysis , 1990 .

[18]  Peter W. Glynn,et al.  Likelihood ratio gradient estimation for stochastic systems , 1990, CACM.

[19]  Pierre Priouret,et al.  Adaptive Algorithms and Stochastic Approximations , 1990, Applications of Mathematics.

[20]  Y. Wardi.  Stochastic algorithms with armijo stepsizes for minimization of functions , 1990 .

[21]  P. Varaiya.  Convergence of a Stochastic Approximation Algorithm for the GI / G / 1 Queue Using Infinitesimal Perturbation Analysis , 1990 .

[22]  Paul Glasserman,et al.  Gradient Estimation Via Perturbation Analysis , 1990 .

[23]  Lee W. Schruben,et al.  Retrospective simulation response optimization , 1991, 1991 Winter Simulation Conference Proceedings..

[24]  Xi-Ren Cao,et al.  Perturbation analysis of discrete event dynamic systems , 1991 .

[25]  Pierre L'Ecuyer,et al.  An overview of derivative estimation , 1991, 1991 Winter Simulation Conference Proceedings..

[26]  S. Mitter,et al.  Recursive stochastic algorithms for global optimization in R d , 1991 .

[27]  G. Yin.  On extensions of Polyak's averaging approach to stochastic approximation , 1991 .

[28]  Yu-Chi Ho,et al.  Ordinal optimization of DEDS , 1992, Discret. Event Dyn. Syst..

[29]  Jorge Haddock,et al.  Simulation optimization using simulated annealing , 1992 .

[30]  Boris Polyak,et al.  Acceleration of stochastic approximation by averaging , 1992 .

[31]  G. Pflug,et al.  Stochastic approximation and optimization of random systems , 1992 .

[32]  D. Yan,et al.  Stochastic discrete optimization , 1992 .

[33]  J. Spall.  Multivariate stochastic approximation using a simultaneous perturbation gradient approximation , 1992 .

[34]  H. Kushner,et al.  Stochastic approximation with averaging of the iterates: Optimal asymptotic rate of convergence for , 1993 .

[35]  P. Glynn,et al.  Stochastic Optimization by Simulation: Convergence Proofs for the GI/G/1 Queue in Steady-State , 1994 .

[36]  E. Chong,et al.  Optimization of queues using an infinitesimal perturbation analysis-based stochastic algorithm with general update times , 1993 .

[37]  Bernard Delyon,et al.  Accelerated Stochastic Approximation , 1993, SIAM J. Optim..

[38]  G. Pflug.  Adaptive Design in Discrete Stochastic Optimization , 1994 .

[39]  Sheldon H. Jacobson,et al.  Convergence Results for Harmonic Gradient Estimators , 1994, INFORMS J. Comput..

[40]  Charles Leake,et al.  Discrete Event Systems: Sensitivity Analysis and Stochastic Optimization by the Score Function Method , 1994 .

[41]  Michael C. Fu,et al.  Optimization via simulation: A review , 1994, Ann. Oper. Res..

[42]  Jason H. Goodfriend,et al.  Discrete Event Systems: Sensitivity Analysis and Stochastic Optimization by the Score Function Method , 1995 .

[43]  B. Fox,et al.  Probabilistic Search with Overrides , 1995 .

[44]  S. Andradóttir.  A method for discrete stochastic optimization , 1995 .

[45]  Sigrún Andradóttir,et al.  A Stochastic Approximation Algorithm with Varying Bounds , 1995, Oper. Res..

[46]  Georg Ch. Pflug,et al.  Confidence sets for discrete stochastic optimization , 1995, Ann. Oper. Res..

[47]  A. Shapiro,et al.  Convergence analysis of gradient descent stochastic algorithms , 1996 .

[48]  Stephen M. Robinson,et al.  Sample-path optimization of convex stochastic performance functions , 1996, Math. Program..

[49]  Yorai Wardi,et al.  Convergence Analysis of Stochastic Algorithms , 1996, Math. Oper. Res..

[50]  S. Andradóttir.  A Scaled Stochastic Approximation Algorithm , 1996 .

[51]  Sigrún Andradóttir,et al.  A Global Search Method for Discrete Stochastic Optimization , 1996, SIAM J. Optim..

[52]  Georg Ch. Pflug,et al.  Simulated Annealing for noisy cost functions , 1996, J. Glob. Optim..

[53]  Stephen M. Robinson,et al.  Analysis of Sample-Path Optimization , 1996, Math. Oper. Res..

[54]  S. Andradóttir.  Optimization of the transient and steady state behavior of discrete event systems , 1996 .

[55]  Jack P. C. Kleijnen,et al.  Experimental Design for Sensitivity Analysis, Optimization and Validation of Simulation Models , 1997 .

[56]  Michael C. Fu,et al.  Conditional Monte Carlo , 1997 .

[57]  Andrzej Ruszczynski,et al.  On Optimal Allocation of Indivisibles Under Uncertainty , 1998, Oper. Res..

[58]  A Orman,et al.  Optimization of Stochastic Models: The Interface Between Simulation and Optimization , 2012, J. Oper. Res. Soc..

[59]  S. Andradóttir,et al.  A Simulated Annealing Algorithm with Constant Temperature for Discrete Stochastic Optimization , 1999 .

[60]  Sigrún Andradóttir,et al.  Accelerating the convergence of random search methods for discrete stochastic optimization , 1999, TOMC.

[61]  Yu-Chi Ho,et al.  Stochastic Comparison Algorithm for Discrete Optimization with Estimation , 1999, SIAM J. Optim..