Abstract: Fully sequential indifference-zone selection procedures have been proposed in the simulation literature to select the system with the best mean performance from a group of simulated systems. However, the existing sequential indifference-zone procedures allocate an equal number of samples to the two systems in comparison even if their variances are drastically different. In this paper we propose new fully sequential indifference-zone procedures that allocate samples according to the variances. We show that the procedures work better than several existing sequential indifference-zone procedures when variances of the system
Sequential sampling problems arise in stochastic simulation and many other applications. Sampling is...
Statistical selection procedures can identify the best of a finite set of alternatives, where “best ...
Many ranking-and-selection (R&S) procedures have been invented for choosing the best simulated s...
Statistical ranking and selection (R&S) is a collection of experiment design and analysis techniques...
We present two fully sequential indifference-zone procedures to select the best sys-tem from a numbe...
Statistical ranking and selection (R&S) is a collection of experiment design and analysis techniques...
[[abstract]]In this paper, we address the problem of finding the simulated system with the best (max...
We consider the indifference-zone (IZ) formulation of the ranking and selection problem in which the...
Two-stage selection procedures have been widely studied and applied to determine appropri-ate sample...
Fully sequential selection procedures have been developed in the field of stochastic simulation to f...
This paper discusses a selection criterion that generalizes the well-known concept of indifference z...
This paper presents a selection procedure that combines Bechhofer's indifference zone selection and ...
Statistical selection is discussed in general terms. In a certain selection procedures are often mor...
We have k “alternatives ” or “systems ” that can be simulated. e.g., different methods for operating...
In this paper, we develop a ranking and selection procedure for making multiple comparisons of syste...
Sequential sampling problems arise in stochastic simulation and many other applications. Sampling is...
Statistical selection procedures can identify the best of a finite set of alternatives, where “best ...
Many ranking-and-selection (R&S) procedures have been invented for choosing the best simulated s...
Statistical ranking and selection (R&S) is a collection of experiment design and analysis techniques...
We present two fully sequential indifference-zone procedures to select the best sys-tem from a numbe...
Statistical ranking and selection (R&S) is a collection of experiment design and analysis techniques...
[[abstract]]In this paper, we address the problem of finding the simulated system with the best (max...
We consider the indifference-zone (IZ) formulation of the ranking and selection problem in which the...
Two-stage selection procedures have been widely studied and applied to determine appropri-ate sample...
Fully sequential selection procedures have been developed in the field of stochastic simulation to f...
This paper discusses a selection criterion that generalizes the well-known concept of indifference z...
This paper presents a selection procedure that combines Bechhofer's indifference zone selection and ...
Statistical selection is discussed in general terms. In a certain selection procedures are often mor...
We have k “alternatives ” or “systems ” that can be simulated. e.g., different methods for operating...
In this paper, we develop a ranking and selection procedure for making multiple comparisons of syste...
Sequential sampling problems arise in stochastic simulation and many other applications. Sampling is...
Statistical selection procedures can identify the best of a finite set of alternatives, where “best ...
Many ranking-and-selection (R&S) procedures have been invented for choosing the best simulated s...