Comparing systems via stochastic simulation: an enhanced two-stage selection procedure
Proceedings of the 32nd conference on Winter simulation
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Proceedings of the 33nd conference on Winter simulation
A Comparison of Evolution Strategies with Other Direct Search Methods in the Presence of Noise
Computational Optimization and Applications
Feature Article: Optimization for simulation: Theory vs. Practice
INFORMS Journal on Computing
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Using Ranking and Selection to "Clean Up" after Simulation Optimization
Operations Research
Simulation optimization: simulation-based optimization
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Recent advances in simulation optimization: a conservative adjustment to the ETSS procedure
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Indifference zone selection procedures: inferences from indifference-zone selection procedures
Proceedings of the 35th conference on Winter simulation: driving innovation
DSN '05 Proceedings of the 2005 International Conference on Dependable Systems and Networks
Combined pattern search and ranking and selection for simulation optimization
WSC '04 Proceedings of the 36th conference on Winter simulation
On the robustness of population-based versus point-basedoptimization in the presence of noise
IEEE Transactions on Evolutionary Computation
Combining Response Surface Methodology with Numerical Methods for Optimization of Markovian Models
IEEE Transactions on Dependable and Secure Computing
OPEDo: a tool framework for modeling and optimization of stochastic models
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
On-line instrumentation for simulation-based optimization
Proceedings of the 38th conference on Winter simulation
Indifference-zone subset selection procedures: using sample means to improve efficiency
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Proceedings of the 40th Conference on Winter Simulation
OPEDo: a tool for the optimization of performance and dependability models
ACM SIGMETRICS Performance Evaluation Review
Optimal computing budget allocation for small computing budgets
Proceedings of the Winter Simulation Conference
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In this paper, we present an evolution strategy for the optimization of simulation models. Our approach incorporates statistical selection procedures that efficiently select the best individual, where best is defined by the maximum or minimum expected simulation response. We use statistical procedures for the survivor selection during the evolutionary process and for selecting the best individual from a set of candidate best individuals, a so-called elite population, at the end of the evolutionary process. Furthermore, we propose a heuristic selection procedure that reduces a random-size subset, containing the best individual, to at most a predefined size. By means of a stochastic sphere function and a simulation model of a production line, we show that this procedure performs better in terms of number of model evaluations and solution quality than other state-of-the-art statistical selection procedures.