Approximation to optimization problems: an elementary review
Mathematics of Operations Research
Mathematical Programming: Series A and B
A nonsmooth version of Newton's method
Mathematical Programming: Series A and B
Asymptotic theory for solutions in statistical estimation and stochastic programming
Mathematics of Operations Research
Simulation optimization of (s,S) inventory systems
WSC '92 Proceedings of the 24th conference on Winter simulation
Sample-path optimization in simulation
WSC '94 Proceedings of the 26th conference on Winter simulation
Convergence analysis of gradient descent stochastic algorithms
Journal of Optimization Theory and Applications
Sample-path optimization of convex stochastic performance functions
Mathematical Programming: Series A and B
Estimating security price derivatives using simulation
Management Science
Analysis of sample-path optimization
Mathematics of Operations Research
Convergence analysis of stochastic algorithms
Mathematics of Operations Research
Retrospective simulation response optimization
WSC '91 Proceedings of the 23rd conference on Winter simulation
Simulation optimization: methods and applications
Proceedings of the 29th conference on Winter simulation
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
A NOTE ON PERTURBATION ANALYSIS ESTIMATORS FOR AMERICAN-STYLE OPTIONS
Probability in the Engineering and Informational Sciences
Solving stochastic mathematical programs with complementarity constraints using simulation
WSC '04 Proceedings of the 36th conference on Winter simulation
Optimal Threshold Levels in Stochastic Fluid Models via Simulation-based Optimization
Discrete Event Dynamic Systems
Solving Stochastic Mathematical Programs with Complementarity Constraints Using Simulation
Mathematics of Operations Research
Expected Residual Minimization Method for Stochastic Linear Complementarity Problems
Mathematics of Operations Research
Hi-index | 0.00 |
This paper shows how to apply a variant of sample path optimization to solve stochastic variational in equalities, including as a special case finding a zero of a gradient. We give a new set of sufficient conditions for almost-sure convergence of the method, and exhibit bounds on the error of the resulting approximate solution. We also illustrate the application of this method by using it to price an American call option on a dividend-paying stock.