### Abstract

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

Pages (from-to) | 495-501 |

Number of pages | 7 |

Journal | Journal of Information and Optimization Sciences |

Volume | 39 |

Issue number | 2 |

DOIs | |

Publication status | Published - 8 Mar 2018 |

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### Cite this

*Journal of Information and Optimization Sciences*,

*39*(2), 495-501. https://doi.org/10.1080/02522667.2017.1378420

}

*Journal of Information and Optimization Sciences*, vol. 39, no. 2, pp. 495-501. https://doi.org/10.1080/02522667.2017.1378420

**Stochastic fractional programming for minimizing variability.** / Gupta, S. N.; Mudaliar, Rajnesh; Kumar, Kuldeep.

Research output: Contribution to journal › Article › Research › peer-review

TY - JOUR

T1 - Stochastic fractional programming for minimizing variability

AU - Gupta, S. N.

AU - Mudaliar, Rajnesh

AU - Kumar, Kuldeep

PY - 2018/3/8

Y1 - 2018/3/8

N2 - In situations where risk aversion is involved, minimization of the variability of the economic criterion under consideration is indispensable. This paper provides a typical stochastic fractional programming model for minimizing the absolute value of the coefficient of variation of a linear function of decision variables under the assumption that the coefficient parameters of the decision variables have a known multivariate normal probability distribution. The stochastic problem is shown to be equivalent to a deterministic problem whose solution can be obtained by solving a related quadratic programming problem.

AB - In situations where risk aversion is involved, minimization of the variability of the economic criterion under consideration is indispensable. This paper provides a typical stochastic fractional programming model for minimizing the absolute value of the coefficient of variation of a linear function of decision variables under the assumption that the coefficient parameters of the decision variables have a known multivariate normal probability distribution. The stochastic problem is shown to be equivalent to a deterministic problem whose solution can be obtained by solving a related quadratic programming problem.

U2 - 10.1080/02522667.2017.1378420

DO - 10.1080/02522667.2017.1378420

M3 - Article

VL - 39

SP - 495

EP - 501

JO - Journal of Information and Optimization Sciences

JF - Journal of Information and Optimization Sciences

SN - 0252-2667

IS - 2

ER -