Selecting the best system: a decision-theoretic approach
Proceedings of the 29th conference on Winter simulation
An integrated framework for deterministic and stochastic optimization
Proceedings of the 29th conference on Winter simulation
A review of simulation optimization techniques
Proceedings of the 30th conference on Winter simulation
Statistical screening, selection, and multiple comparison procedures in computer simulation
Proceedings of the 30th conference on Winter simulation
Iterative ranking-and-selection for large-scale optimization
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
A decision-theoretic approach to screening and selection with common random numbers
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
New results on procedures that select the best system using CRN
Proceedings of the 32nd conference on Winter simulation
Optimization and system selection: simulation/optimization using "real-world" applications
Proceedings of the 33nd conference on Winter simulation
Simulation optimization: towards a framework for black-box simulation optimization
Proceedings of the 33nd conference on Winter simulation
Nested Partitions Method for Global Optimization
Operations Research
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The nested partitions method is a flexible and effective framework of optimizing large-scale problems with combinatorial structure. In this paper we consider the nested partitions method for simulation optimization and propose a new variant that uses inheritance to speed convergence. The new nested partitions method with inheritance algorithm performs well for when applied to test problems but it also calls for new analysis of convergence.