### Abstract

In real-world applications, sometimes randomness and fuzziness may coexist. In facility-location problems, the data expressed in natural language may contain vague information. We discuss the uncertainty included in demands in facility-location problems. The uncertain demand is called fuzzy demand in this paper. In the facility-location model, the parameters of fuzzy demand are determined by calculating the estimated expected value of the fuzzy demand, which is obtained by using the estimated parameters of the underlying probability distribution function of the fuzzy data. Moreover, we propose a defuzzification formula of the fuzzy demand called the realization of fuzzy demand. The defuzzification formula of fuzzy demand comprises the upper bound and the lower bound of the fuzzy demand. Moreover, the error of the fuzzy demand is assessed as the mean absolute percentage error of the fuzzy demand. Empirical studies show that we can solve real-life location problems by using the defuzzification formula of fuzzy demand and get higher profit in our facility-location model than by using conventional methods.

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

Pages (from-to) | 484-493 |

Number of pages | 10 |

Journal | IEEJ Transactions on Electrical and Electronic Engineering |

Volume | 9 |

Issue number | 5 |

DOIs | |

Publication status | Published - 2014 |

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### Keywords

- Fuzzy data
- Fuzzy statistic
- Location decision
- Probability distribution function
- Uncertain demand

### ASJC Scopus subject areas

- Electrical and Electronic Engineering

### Cite this

*IEEJ Transactions on Electrical and Electronic Engineering*,

*9*(5), 484-493. https://doi.org/10.1002/tee.21997

**A parametric assessment approach to solving facility-location problems with fuzzy demands.** / Lin, Pei Chun; Watada, Junzo; Wu, Berlin.

Research output: Contribution to journal › Article

*IEEJ Transactions on Electrical and Electronic Engineering*, vol. 9, no. 5, pp. 484-493. https://doi.org/10.1002/tee.21997

}

TY - JOUR

T1 - A parametric assessment approach to solving facility-location problems with fuzzy demands

AU - Lin, Pei Chun

AU - Watada, Junzo

AU - Wu, Berlin

PY - 2014

Y1 - 2014

N2 - In real-world applications, sometimes randomness and fuzziness may coexist. In facility-location problems, the data expressed in natural language may contain vague information. We discuss the uncertainty included in demands in facility-location problems. The uncertain demand is called fuzzy demand in this paper. In the facility-location model, the parameters of fuzzy demand are determined by calculating the estimated expected value of the fuzzy demand, which is obtained by using the estimated parameters of the underlying probability distribution function of the fuzzy data. Moreover, we propose a defuzzification formula of the fuzzy demand called the realization of fuzzy demand. The defuzzification formula of fuzzy demand comprises the upper bound and the lower bound of the fuzzy demand. Moreover, the error of the fuzzy demand is assessed as the mean absolute percentage error of the fuzzy demand. Empirical studies show that we can solve real-life location problems by using the defuzzification formula of fuzzy demand and get higher profit in our facility-location model than by using conventional methods.

AB - In real-world applications, sometimes randomness and fuzziness may coexist. In facility-location problems, the data expressed in natural language may contain vague information. We discuss the uncertainty included in demands in facility-location problems. The uncertain demand is called fuzzy demand in this paper. In the facility-location model, the parameters of fuzzy demand are determined by calculating the estimated expected value of the fuzzy demand, which is obtained by using the estimated parameters of the underlying probability distribution function of the fuzzy data. Moreover, we propose a defuzzification formula of the fuzzy demand called the realization of fuzzy demand. The defuzzification formula of fuzzy demand comprises the upper bound and the lower bound of the fuzzy demand. Moreover, the error of the fuzzy demand is assessed as the mean absolute percentage error of the fuzzy demand. Empirical studies show that we can solve real-life location problems by using the defuzzification formula of fuzzy demand and get higher profit in our facility-location model than by using conventional methods.

KW - Fuzzy data

KW - Fuzzy statistic

KW - Location decision

KW - Probability distribution function

KW - Uncertain demand

UR - http://www.scopus.com/inward/record.url?scp=84906225653&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84906225653&partnerID=8YFLogxK

U2 - 10.1002/tee.21997

DO - 10.1002/tee.21997

M3 - Article

VL - 9

SP - 484

EP - 493

JO - IEEJ Transactions on Electrical and Electronic Engineering

JF - IEEJ Transactions on Electrical and Electronic Engineering

SN - 1931-4973

IS - 5

ER -