Journal ArticleDOI
A fully sequential procedure for indifference-zone selection in simulation
Seong-Hee Kim,Barry L. Nelson +1 more
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The procedures presented are appropriate when it is possible to repeatedly obtain small, incremental samples from each simulated system and are based on the assumption of normally distributed data, so the impact of batching is analyzed.Abstract:
We present procedures for selecting the best or near-best of a finite number of simulated systems when best is defined by maximum or minimum expected performance. The procedures are appropriate when it is possible to repeatedly obtain small, incremental samples from each simulated system. The goal of such a sequential procedure is to eliminate, at an early stage of experimentation, those simulated systems that are apparently inferior, and thereby reduce the overall computational effort required to find the best. The procedures we present accommodate unequal variances across systems and the use of common random numbers. However, they are based on the assumption of normally distributed data, so we analyze the impact of batching (to achieve approximate normality or independence) on the performance of the procedures. Comparisons with some existing indifference-zone procedures are also provided.read more
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Parameter tuning for configuring and analyzing evolutionary algorithms
Agoston E. Eiben,S.K. Smit +1 more
TL;DR: A conceptual framework for parameter tuning is presented, a survey of tuning methods is provided, and related methodological issues are discussed to elaborate on how tuning can improve methodology by facilitating well-funded experimental comparisons and algorithm analysis.
Journal ArticleDOI
A Knowledge-Gradient Policy for Sequential Information Collection
TL;DR: In a sequential Bayesian ranking and selection problem with independent normal populations and common known variance, a previously introduced measurement policy is studied, showing that the knowledge-gradient policy is optimal both when the horizon is a single time period and in the limit as the horizon extends to infinity.
Journal ArticleDOI
The Knowledge-Gradient Policy for Correlated Normal Beliefs
TL;DR: A fully sequential sampling policy is proposed called the knowledge-gradient policy, which is provably optimal in some special cases and has bounded suboptimality in all others and it is demonstrated how this policy may be applied to efficiently maximize a continuous function on a continuous domain while constrained to a fixed number of noisy measurements.
Journal ArticleDOI
Multiple Comparisons: Theory and Methods
TL;DR: In this paper, the authors present a comparison of multiple comparative methods in theory and methods for quality assurance in the field of quality assurance. Journal of Quality Technology: Vol. 29, No. 3, No 3, pp. 359-359.
Journal ArticleDOI
Simulation optimization for an emergency department healthcare unit in Kuwait
TL;DR: Experimental results show that by using current hospital resources, the optimization simulation model generates optimal staffing allocation that would allow 28% increase in patient throughput and an average of 40% reduction in patients' waiting time.
References
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Book
Multiple Comparison Procedures
Yosef Hochberg,Ajit C. Tamhane +1 more
TL;DR: In this article, a theory of multiple comparison problems is presented, along with a procedure for pairwise and more general comparisons among all treatments among all the treatments in a clinical trial.
Journal ArticleDOI
On two-stage selection procedures and related probability-inequalities
TL;DR: In this article, a modification of the Dudewicz-Dalal procedure for the problem of selecting the population with the largest mean from k normal populations with unknown variances is discussed.
Journal ArticleDOI
Multiple Comparisons: Theory and Methods
TL;DR: In this paper, the authors present a comparison of multiple comparative methods in theory and methods for quality assurance in the field of quality assurance. Journal of Quality Technology: Vol. 29, No. 3, No 3, pp. 359-359.