A lower bound for the correct subset-selection probability and its application to discrete-event system simulations
- 1 January 1996
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Automatic Control
- Vol. 41 (8) , 1227-1231
- https://doi.org/10.1109/9.533692
Abstract
Ordinal optimization concentrates on finding a subset of good designs, by approximately evaluating a parallel set of designs, and reduces the required simulation time dramatically for discrete-event simulation and optimization. The estimation of the confidence probability (CP) that the selected designs contain at least one good design is crucial to ordinal optimization. However, it is very difficult to estimate this probability in DES simulation, especially for complicated DES with large number of designs. This paper proposes two simple lower bounds for quantifying the confidence probability. Numerical testing is presented.Keywords
This publication has 6 references indexed in Scilit:
- Ranking, selection and multiple comparisons in computer simulationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Methods for selecting the best system (for simulation)Published by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- SIMD parallel discrete-event dynamic system simulationIEEE Transactions on Control Systems Technology, 1997
- An approximation approach of the standard clock method for general discrete-event simulationIEEE Transactions on Control Systems Technology, 1995
- Ordinal optimization of DEDSDiscrete Event Dynamic Systems, 1992
- Using a standard clock technique for efficient simulationOperations Research Letters, 1991