Convergence of an annealing algorithm
Mathematical Programming: Series A and B
Optimization of stochastic systems via simulation
WSC '89 Proceedings of the 21st conference on Winter simulation
Neural network models in simulation: a comparison with traditional modeling approaches
WSC '89 Proceedings of the 21st conference on Winter simulation
Simulation optimization using simulated annealing
Computers and Industrial Engineering
Metamodels for simulation input-output relations
WSC '92 Proceedings of the 24th conference on Winter simulation
A tutorial review of techniques for simulation optimization
WSC '94 Proceedings of the 26th conference on Winter simulation
Buffer size optimization in asynchronous assembly systems using genetic algorithms
Computers and Industrial Engineering
Simulation optimization: methods and applications
Proceedings of the 29th conference on Winter simulation
Optimizing discrete stochastic systems using simulated annealing and simulation
Computers and Industrial Engineering - Special issue: new advances in analysis of manufacturing systems
WSC '88 Proceedings of the 20th conference on Winter simulation
Optimization in simulation: a survey of recent results
WSC '87 Proceedings of the 19th conference on Winter simulation
Simulation optimization methodologies
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Simulation optimization: a survey of simulation optimization techniques and procedures
Proceedings of the 32nd conference on Winter simulation
Empirical comparison of search algorithms for discrete event simulation
Computers and Industrial Engineering
Manufacturing analysis and control: buffer allocation model based on a single simulation
Proceedings of the 35th conference on Winter simulation: driving innovation
Intelligent modeling and simulation of flexible assembly systems
WSC '05 Proceedings of the 37th conference on Winter simulation
Simulation intelligence and modeling for manufacturing uncertainties
Proceedings of the 38th conference on Winter simulation
International Journal of Decision Support System Technology
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When the systems under investigation are complex, the analytical solutions to these systems become impossible. Because of the complex stochastic characteristics of the systems, simulation can be used as an analysis tool to predict the performance of an existing system or a design tool to test new systems under varying circumstances. However, simulation is extremely time consuming for most problems of practical interest. As a result, it is impractical to perform any parametric study of system performance, especially for systems with a large parameter space. One approach to overcome this limitation is to develop a simpler model to explain the relationship between the inputs and outputs of the system. Simulation metamodels are increasingly being used in conjunction with the original simulation, to improve the analysis and understanding of decision-making processes. In this study, artificial neural networks (ANN) metamodel is developed for simulation model of an asynchronous assembly system and ANN metamodel together with simulated annealing (SA) is used to optimize the buffer sizes in the system.