A new polynomial-time algorithm for linear programming
Combinatorica
Optimization of stochastic systems
WSC '86 Proceedings of the 18th conference on Winter simulation
Stochastic approximation for Monte Carlo optimization
WSC '86 Proceedings of the 18th conference on Winter simulation
Strategies for optimization of multiple-response simulation models
WSC '77 Proceedings of the 9th conference on Winter simulation - Volume 1
Factor screening of multiple responses
WSC '92 Proceedings of the 24th conference on Winter simulation
A tutorial on simulation optimization
WSC '92 Proceedings of the 24th conference on Winter simulation
Single run optimization using the reverse-simulation method
Proceedings of the 29th conference on Winter simulation
An overview of derivative estimation
WSC '91 Proceedings of the 23rd conference on Winter simulation
Multicriteria optimization of simulation models
WSC '91 Proceedings of the 23rd conference on Winter simulation
Comparison of global search methods for design optimization using simulation
WSC '91 Proceedings of the 23rd conference on Winter simulation
WSC '88 Proceedings of the 20th conference on Winter simulation
Designing computer simulation experiments
WSC '88 Proceedings of the 20th conference on Winter simulation
WSC '88 Proceedings of the 20th conference on Winter simulation
Performance continuity and differentiability in Monte Carlo optimization
WSC '88 Proceedings of the 20th conference on Winter simulation
Steel product transportation and storage simulation: a combined simulation/optimization approach
WSC '88 Proceedings of the 20th conference on Winter simulation
Simulation optimization methodologies
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
An approach for finding discrete variable design alternatives using a simulation optimization method
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Simulation optimization with the linear move and exchange move optimization algorithm
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Introduction to simulation (tutorial session)
WSC' 90 Proceedings of the 22nd conference on Winter simulation
Finite-time behavior of two simulation optimization algorithms
WSC' 90 Proceedings of the 22nd conference on Winter simulation
Fuzzy controlled simulation optimization
Fuzzy Sets and Systems - Special issue: Approximate Reasoning in Words
Discrete Event Dynamic Systems
Simulation response optimization via direct conjugate direction method
Computers and Operations Research
A sequential-design metamodeling strategy for simulation optimization
Computers and Operations Research
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Optimal Threshold Levels in Stochastic Fluid Models via Simulation-based Optimization
Discrete Event Dynamic Systems
Computational Optimization and Applications
An alternating variable method with varying replications for simulation response optimization
Computers & Mathematics with Applications
Techniques for simulation response optimization
Operations Research Letters
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This paper surveys existing methods, and presents several new ideas, for optimizing performance measures with respect to input parameters for simulation. The usual methods fall into three categories. First, there is the application of traditional non-linear programming techniques, regardless of the stochastic properties of most discrete event simulations. Second, is the application of response surface methodologies. Third, are stochastic approximation techniques, a well known but little used optimization technique. The last two categories account for the stochastic behavior of simulations.This paper also discusses several developments within the past seven years that promise greater efficiency in optimizing simulations. These developments include: Karmarkar's algorithm, infinitesimal perturbation analysis and likelihood ratios to estimate derivatives of performance measures with respect to parameters, adaptive control and hybrid models.