Random search in the presence of noise, with application to machine learning
SIAM Journal on Scientific and Statistical Computing
Stochastic discrete optimization
SIAM Journal on Control and Optimization
Simulation optimization using simulated annealing
Computers and Industrial Engineering
Ranking, selection and multiple comparisons in computer simulations
WSC '94 Proceedings of the 26th conference on Winter simulation
A method for discrete stochastic optimization
Management Science
Methods for selecting the best system
WSC '91 Proceedings of the 23rd conference on Winter simulation
Discrete stochastic optimization via a modification of the stochastic ruler method
WSC '96 Proceedings of the 28th conference on Winter simulation
Simulation optimization: methods and applications
Proceedings of the 29th conference on Winter simulation
Accelerating the convergence of the stochastic ruler method for discrete stochastic optimization
Proceedings of the 29th conference on Winter simulation
Simulation optimization methodologies
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
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We present a new method for finding a global optimal solution to a discrete stochastic optimization problem. This method resembles the simulated annealing method for discrete deterministic optimization. However, in our method the annealing schedule (the cooling temperature) is kept fixed, and the mechanism for estimating the optimal solution is different from that used in the original simulated annealing method. We state a convergence result that shows that our method converges almost surely to a global optimal solution under mild conditions. We also present empirical results that illustrate the performance of the proposed approach on a simple example.