Acceleration of stochastic approximation by averaging
SIAM Journal on Control and Optimization
Asymptotic behavior of optimal solutions in stochastic programming
Mathematics of Operations Research
New advances and applications of combining simulation and optimization
WSC '96 Proceedings of the 28th conference on Winter simulation
Analysis of sample-path optimization
Mathematics of Operations Research
Weighted Means in Stochastic Approximation of Minima
SIAM Journal on Control and Optimization
A branch and bound method for stochastic global optimization
Mathematical Programming: Series A and B
Retrospective simulation response optimization
WSC '91 Proceedings of the 23rd conference on Winter simulation
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Computational Optimization and Applications
Feature Article: Optimization for simulation: Theory vs. Practice
INFORMS Journal on Computing
The Cross Entropy Method: A Unified Approach To Combinatorial Optimization, Monte-carlo Simulation (Information Science and Statistics)
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Lower bound on complexity of optimization of continuous functions
Journal of Complexity
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Assessing solution quality in stochastic programs
Mathematical Programming: Series A and B
Gradient-based simulation optimization
Proceedings of the 38th conference on Winter simulation
Discrete Optimization via Simulation Using COMPASS
Operations Research
Efficient sample sizes in stochastic nonlinear programming
Journal of Computational and Applied Mathematics
A Model Reference Adaptive Search Method for Global Optimization
Operations Research
Monte Carlo bounding techniques for determining solution quality in stochastic programs
Operations Research Letters
The stochastic root-finding problem: Overview, solutions, and open questions
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Better simulation metamodeling: the why, what, and how of stochastic kriging
Winter Simulation Conference
Convergence properties of direct search methods for stochastic optimization
Proceedings of the Winter Simulation Conference
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Continuous-variable simulation optimization problems are those optimization problems where the objective function is computed through stochastic simulation and the decision variables are continuous. We discuss verifiable conditions under which the objective function is continuous or differ-entiable, and outline some key properties of two classes of methods for solving such problems, namely sample-average approximation and stochastic approximation.