Likelihood ratio gradient estimation for stochastic systems
Communications of the ACM - Special issue on simulation
Optimization
Understanding industrial designed experiments (2nd ed.)
Understanding industrial designed experiments (2nd ed.)
A review of simulation optimization techniques
Proceedings of the 30th conference on Winter simulation
Identifying important factors in deterministic investment problems using design of experiments
Proceedings of the 30th conference on Winter simulation
Simulation optimization: a survey of simulation optimization techniques and procedures
Proceedings of the 32nd conference on Winter simulation
Integrating optimization and simulation: research and practice
Proceedings of the 32nd conference on Winter simulation
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Proceedings of the 33nd conference on Winter simulation
A practical bottleneck detection method
Proceedings of the 33nd conference on Winter simulation
Panel: simulation optimization: future of simulation optimization
Proceedings of the 33nd conference on Winter simulation
Manufacturing analysis and control: buffer allocation model based on a single simulation
Proceedings of the 35th conference on Winter simulation: driving innovation
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This paper describes a novel method of calculating the sensitivity of the manufacturing system throughput to the variables of the machines. The sensitivity analysis needs only a single simulation, yet is easy to use and provides accurate results. This sensitivity analysis is then used to predict the change in the system throughput due to a change of the variables of the machines provided that the system change does not significantly change the bottleneck. These predictions can be used for a local optimization, allowing the use of a steepest descent optimization algorithm. The method is based on improving the momentary shifting bottlenecks. The shifting bottlenecks are detected using the shifting bottleneck detection method based on the active duration, i.e., the time a machine is active without interruption. The method is easy to understand and easy to implement in existing simulation software.