### Abstract

In this paper, we discuss the concept of the expected opportunity cost of a potentially incorrect selection as a measure of selection quality on a new selection procedure that is used to selecting the top m systems for large scale problems. This procedure is used the ordinal optimiza- tion method to reduce the size of the search space, and then it is used the idea of computing budget allocation OCBA-m to identify the top m systems from the survivors systems that we got it by ordinal opti- mization method. This procedure is tested on two numerical examples, buffer allocation problem BAP and M/M/1 queuing system. Clearly from the numerical results this procedure selects the optimal subset of systems with the minimum expected opportunity cost of a potentially incorrect selection.

Original language | English |
---|---|

Pages (from-to) | 6507-6519 |

Number of pages | 13 |

Journal | Applied Mathematical Sciences |

Volume | 9 |

Issue number | 131 |

DOIs | |

Publication status | Published - 2015 |

### Fingerprint

### Keywords

- Expected opportunity cost
- Optimal computing budget allocation
- Ordinal optimization
- Simulation optimization

### ASJC Scopus subject areas

- Applied Mathematics

### Cite this

*Applied Mathematical Sciences*,

*9*(131), 6507-6519. https://doi.org/10.12988/ams.2015.58561

**The expected opportunity cost and selecting the optimal subset.** / Almomani, Mohammad H.; Ababneh, Faisal.

Research output: Contribution to journal › Article

*Applied Mathematical Sciences*, vol. 9, no. 131, pp. 6507-6519. https://doi.org/10.12988/ams.2015.58561

}

TY - JOUR

T1 - The expected opportunity cost and selecting the optimal subset

AU - Almomani, Mohammad H.

AU - Ababneh, Faisal

PY - 2015

Y1 - 2015

N2 - In this paper, we discuss the concept of the expected opportunity cost of a potentially incorrect selection as a measure of selection quality on a new selection procedure that is used to selecting the top m systems for large scale problems. This procedure is used the ordinal optimiza- tion method to reduce the size of the search space, and then it is used the idea of computing budget allocation OCBA-m to identify the top m systems from the survivors systems that we got it by ordinal opti- mization method. This procedure is tested on two numerical examples, buffer allocation problem BAP and M/M/1 queuing system. Clearly from the numerical results this procedure selects the optimal subset of systems with the minimum expected opportunity cost of a potentially incorrect selection.

AB - In this paper, we discuss the concept of the expected opportunity cost of a potentially incorrect selection as a measure of selection quality on a new selection procedure that is used to selecting the top m systems for large scale problems. This procedure is used the ordinal optimiza- tion method to reduce the size of the search space, and then it is used the idea of computing budget allocation OCBA-m to identify the top m systems from the survivors systems that we got it by ordinal opti- mization method. This procedure is tested on two numerical examples, buffer allocation problem BAP and M/M/1 queuing system. Clearly from the numerical results this procedure selects the optimal subset of systems with the minimum expected opportunity cost of a potentially incorrect selection.

KW - Expected opportunity cost

KW - Optimal computing budget allocation

KW - Ordinal optimization

KW - Simulation optimization

UR - http://www.scopus.com/inward/record.url?scp=84981187937&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84981187937&partnerID=8YFLogxK

U2 - 10.12988/ams.2015.58561

DO - 10.12988/ams.2015.58561

M3 - Article

AN - SCOPUS:84981187937

VL - 9

SP - 6507

EP - 6519

JO - Applied Mathematical Sciences

JF - Applied Mathematical Sciences

SN - 1312-885X

IS - 131

ER -