Statistical selection procedures are used to select the best simulated system from a finite set of alternatives. In this paper, we present a procedure that can be used to select the best system when the number of alternatives is large. The proposed procedure consists a combination between Ranking and Selection, and Ordinal Optimization procedures. In order to improve the performance of Ordinal Optimization, Optimal Computing Budget Allocation technique is used to determine the best simulation lengths for all simulation systems and to reduce the total computation time. We also argue the effect of increment in simulation samples for the combined procedure. The results of numerical illustration show clearly the effect of increment in simulatio...
Simulation is widely used to identify the best of a finite set of proposed systems, where 'best' is ...
We describe the basic principles of ranking and selection, a collection of experiment-design techniq...
Abstract—In this paper, we consider the effect of the initial sample size on the performance of a se...
In this paper we address the problem of finding the simulated system with the best (maximum or minim...
[[abstract]]In this paper, we address the problem of finding the simulated system with the best (max...
In this paper we address the problem of finding the simulated system with the best (maximum or minim...
Ordinal Optimization has emerged as an efficient technique for simulation and optimization. Exponent...
Ordinal Optimization offers an efficient approach for simulation optimization by focusing on ranking...
We consider a class of the subset selection problem in ranking and selection. The objective is to id...
Selecting a subset of the best solutions among large-scale problems is an important area of research...
In many real-world applications, designs can only be evaluated pairwise, relative to each other. Nev...
Statistical ranking and selection (R&S) is a collection of experiment design and analysis techniques...
The methodology based on computing budget allocation is an effective tool in solving the problem of ...
Statistical ranking and selection (R&S) is a collection of experiment design and analysis techniques...
We consider subset selection problems in ranking and selection with tight computational budgets. We ...
Simulation is widely used to identify the best of a finite set of proposed systems, where 'best' is ...
We describe the basic principles of ranking and selection, a collection of experiment-design techniq...
Abstract—In this paper, we consider the effect of the initial sample size on the performance of a se...
In this paper we address the problem of finding the simulated system with the best (maximum or minim...
[[abstract]]In this paper, we address the problem of finding the simulated system with the best (max...
In this paper we address the problem of finding the simulated system with the best (maximum or minim...
Ordinal Optimization has emerged as an efficient technique for simulation and optimization. Exponent...
Ordinal Optimization offers an efficient approach for simulation optimization by focusing on ranking...
We consider a class of the subset selection problem in ranking and selection. The objective is to id...
Selecting a subset of the best solutions among large-scale problems is an important area of research...
In many real-world applications, designs can only be evaluated pairwise, relative to each other. Nev...
Statistical ranking and selection (R&S) is a collection of experiment design and analysis techniques...
The methodology based on computing budget allocation is an effective tool in solving the problem of ...
Statistical ranking and selection (R&S) is a collection of experiment design and analysis techniques...
We consider subset selection problems in ranking and selection with tight computational budgets. We ...
Simulation is widely used to identify the best of a finite set of proposed systems, where 'best' is ...
We describe the basic principles of ranking and selection, a collection of experiment-design techniq...
Abstract—In this paper, we consider the effect of the initial sample size on the performance of a se...