TY - JOUR

T1 - On the optimal computing budget allocation problem for large scale simulation optimization

AU - Al-Salem, Mohammed

AU - Almomani, Mohammad

AU - Alrefaei, Mahmoud

AU - Diabat, Ali

N1 - Publisher Copyright:
© 2016 Elsevier B.V.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2017/2/1

Y1 - 2017/2/1

N2 - Selecting a set that contains the best simulated systems is an important area of research. When the number of alternative systems is large, then it becomes impossible to simulate all alternatives, so one needs to relax the problem in order to find a good enough simulated system rather than simulating each alternative. One way for solving this problem is to use two-stage sequential procedure. In the first stage the ordinal optimization is used to select a subset that overlaps with the actual best systems with high probability. Then in the second stage an optimization procedure can be applied on the smaller set to select the best alternatives in it. In this paper, we consider the optimal computing budget allocation (OCBA) in the second stage that distribute available computational budget on the alternative systems in order to get a correct selection with high probability. We also discuss the effect of the simulation parameters on the performance of the procedure by implementing the procedure on three different examples. The numerical results indeed indicate that the choice of these parameters affect its performance.

AB - Selecting a set that contains the best simulated systems is an important area of research. When the number of alternative systems is large, then it becomes impossible to simulate all alternatives, so one needs to relax the problem in order to find a good enough simulated system rather than simulating each alternative. One way for solving this problem is to use two-stage sequential procedure. In the first stage the ordinal optimization is used to select a subset that overlaps with the actual best systems with high probability. Then in the second stage an optimization procedure can be applied on the smaller set to select the best alternatives in it. In this paper, we consider the optimal computing budget allocation (OCBA) in the second stage that distribute available computational budget on the alternative systems in order to get a correct selection with high probability. We also discuss the effect of the simulation parameters on the performance of the procedure by implementing the procedure on three different examples. The numerical results indeed indicate that the choice of these parameters affect its performance.

KW - Large scale problems

KW - Optimal computing budget allocation

KW - Ordinal optimization

KW - Simulation optimization

UR - http://www.scopus.com/inward/record.url?scp=85003451712&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85003451712&partnerID=8YFLogxK

U2 - 10.1016/j.simpat.2016.05.004

DO - 10.1016/j.simpat.2016.05.004

M3 - Article

AN - SCOPUS:85003451712

VL - 71

SP - 149

EP - 159

JO - Simulation Modelling Practice and Theory

JF - Simulation Modelling Practice and Theory

SN - 1569-190X

ER -