Genetic algorithms: foundations and applications
Annals of Operations Research
Stochastic discrete optimization
SIAM Journal on Control and Optimization
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
Optimizing discrete stochastic systems using simulated annealing and simulation
Computers and Industrial Engineering - Special issue: new advances in analysis of manufacturing systems
Proceedings of the 33nd conference on Winter simulation
The Sample Average Approximation Method for Stochastic Discrete Optimization
SIAM Journal on Optimization
Feature Article: Optimization for simulation: Theory vs. Practice
INFORMS Journal on Computing
Finding the best in the presence of a stochastic constraint
WSC '05 Proceedings of the 37th conference on Winter simulation
Discrete Optimization via Simulation Using COMPASS
Operations Research
Finding feasible systems in the presence of constraints on multiple performance measures
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Optimal computing budget allocation for constrained optimization
Winter Simulation Conference
Stochastic approximation of constrained systems with system and constraint noise
Automatica (Journal of IFAC)
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We consider a constrained optimization problem over a discrete set where noise--corrupted observations of the objective and constraints are available. The problem is challenging because the feasibility of a solution cannot be known for certain, due to the noisy measurements of the constraints. To tackle this issue, we propose a new method that converts constrained optimization into the unconstrained optimization problem of finding a saddle point of the Lagrangian. The method applies stochastic approximation to the Lagrangian in search of the saddle point. The proposed method is shown to converge, under suitable conditions, to the optimal solution almost surely (a.s.) as the number of iterations grows. We present the effectiveness of the proposed method numerically in two settings: (1) inventory control in a periodic review system, and (2) staffing in a call center.