A procedure for selecting a subset of size m containing the l best of k independent normal populations, with applications to simulation

DOI10.1080/03610918508812467zbMath0576.62036OpenAlexW2029530218MaRDI QIDQ3696306

Averill M. Law, Lloyd W. Koenig

Publication date: 1985

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918508812467

zbMATH Keywords

Discrete event simulationprobability of correct selectionindifference zone approachindependent normal populationstwo-stage sampling procedure

Mathematics Subject Classification ID

Statistical ranking and selection procedures (62F07)

Related Items (16)

Finding Feasible Systems for Subjective Constraints Using Recycled Observations ⋮ Rapid Discrete Optimization via Simulation with Gaussian Markov Random Fields ⋮ Designing selection experiments with bernoulli populations ⋮ An efficient simulation procedure for the expected opportunity cost using metamodels ⋮ Efficient subset selection for the expected opportunity cost ⋮ Good arm identification via bandit feedback ⋮ A New Budget Allocation Framework for the Expected Opportunity Cost ⋮ Selecting the best simulated system with weighted control-variate estimators ⋮ Input–Output Uncertainty Comparisons for Discrete Optimization via Simulation ⋮ A new approach to estimate the critical constant of selection procedures ⋮ A sequential procedure for neighborhood selection-of-the-best in optimization via simulation ⋮ Penalty Function with Memory for Discrete Optimization via Simulation with Stochastic Constraints ⋮ A multi-objective selection procedure of determining a Pareto set ⋮ Gaussian Markov Random Fields for Discrete Optimization via Simulation: Framework and Algorithms ⋮ Efficient simulation budget allocation for ranking the top \(m\) designs ⋮ Optimal budget allocation policy for tabu search in stochastic simulation optimization

Cites Work

• Unnamed Item
• Some Fixed-Sample Ranking and Selection Problems
• A Single-Sample Multiple Decision Procedure for Ranking Means of Normal Populations with known Variances
• A Two-Sample Test for a Linear Hypothesis Whose Power is Independent of the Variance

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