Fundamentals of queueing theory (2nd ed.).
Fundamentals of queueing theory (2nd ed.).
Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Computers and Operations Research
Response surface methodology: 1966–1988
Technometrics
Simulation optimization using simulated annealing
Computers and Industrial Engineering
A tutorial on simulation optimization
WSC '92 Proceedings of the 24th conference on Winter simulation
Simulation optimization by genetic search
Mathematics and Computers in Simulation
Comparison of gradient estimation techniques for queues with non-identical servers
Computers and Operations Research
Genetic algorithms in optimizing simulated systems
WSC '95 Proceedings of the 27th conference on Winter simulation
Nelder-Mead simplex modifications for simulation optimization
Management Science
A scaled stochastic approximation algorithm
Management Science
A one-measurement form of simultaneous perturbation stochastic approximation
Automatica (Journal of IFAC)
Optimization of stochastic systems
WSC '86 Proceedings of the 18th conference on Winter simulation
Optimization in simulation: a survey of recent results
WSC '87 Proceedings of the 19th conference on Winter simulation
Testing Unconstrained Optimization Software
ACM Transactions on Mathematical Software (TOMS)
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This paper modifies Powell's conjugate direction method for unconstrained, continuous, local optimization problems to adapt to the stochastic environment in simulation response optimization. The main idea underlying the proposed method is to conduct several replications at each trial point to obtain reliable estimate of the theoretical response. To avoid misjudging the real difference between two points due to the stochastic nature, a t-test of the statistical hypothesis is employed to replace the simple comparison of the mean responses. In an experimental comparison, the proposed method outperforms the Nelder-Mead simlex method, a quasi-Newton method, and several other methods in solving a stochastic Watson function with nine variables, a queueing problem with two variables, and an inventory problem with two variables.