### Abstract

This paper considers an expectation optimization model using a possibility measure to the objective function in the fuzzy random programming problem, based on possibilistic programming and stochastic programming. The main fuzzy random programming problem is not a well-defined problem due to including random variables and fuzzy numbers. Therefore, in order to solve it analytically, a criterion for goal of objective function is set and the chance constraint are introduced. Then, considering decision maker's subjectivity and flexibility of the original plan, a fuzzy goal for each objective function is introduced. Furthermore, this paper considers that the occurrence probability of each scenario has ambiguity, and is represented as an interval value. Considering this interval of probability, a robust expectation optimization problem is proposed. Main problem is transformed into the deterministic equivalent linear programming problem, and so the analytical solution method extending previous solution approaches is constructed.

Original language | English |
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Title of host publication | Advances in Intelligent and Soft Computing |

Publisher | Springer Verlag |

Pages | 285-294 |

Number of pages | 10 |

Volume | 58 |

ISBN (Print) | 9783540896180 |

Publication status | Published - 2009 |

Externally published | Yes |

### Publication series

Name | Advances in Intelligent and Soft Computing |
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Volume | 58 |

ISSN (Print) | 18675662 |

### Fingerprint

### ASJC Scopus subject areas

- Computer Science(all)

### Cite this

*Advances in Intelligent and Soft Computing*(Vol. 58, pp. 285-294). (Advances in Intelligent and Soft Computing; Vol. 58). Springer Verlag.

**Robust expectation optimization model using the possibility measure for the fuzzy random programming problem.** / Hasuike, Takashi; Ishii, Hiroaki.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Advances in Intelligent and Soft Computing.*vol. 58, Advances in Intelligent and Soft Computing, vol. 58, Springer Verlag, pp. 285-294.

}

TY - GEN

T1 - Robust expectation optimization model using the possibility measure for the fuzzy random programming problem

AU - Hasuike, Takashi

AU - Ishii, Hiroaki

PY - 2009

Y1 - 2009

N2 - This paper considers an expectation optimization model using a possibility measure to the objective function in the fuzzy random programming problem, based on possibilistic programming and stochastic programming. The main fuzzy random programming problem is not a well-defined problem due to including random variables and fuzzy numbers. Therefore, in order to solve it analytically, a criterion for goal of objective function is set and the chance constraint are introduced. Then, considering decision maker's subjectivity and flexibility of the original plan, a fuzzy goal for each objective function is introduced. Furthermore, this paper considers that the occurrence probability of each scenario has ambiguity, and is represented as an interval value. Considering this interval of probability, a robust expectation optimization problem is proposed. Main problem is transformed into the deterministic equivalent linear programming problem, and so the analytical solution method extending previous solution approaches is constructed.

AB - This paper considers an expectation optimization model using a possibility measure to the objective function in the fuzzy random programming problem, based on possibilistic programming and stochastic programming. The main fuzzy random programming problem is not a well-defined problem due to including random variables and fuzzy numbers. Therefore, in order to solve it analytically, a criterion for goal of objective function is set and the chance constraint are introduced. Then, considering decision maker's subjectivity and flexibility of the original plan, a fuzzy goal for each objective function is introduced. Furthermore, this paper considers that the occurrence probability of each scenario has ambiguity, and is represented as an interval value. Considering this interval of probability, a robust expectation optimization problem is proposed. Main problem is transformed into the deterministic equivalent linear programming problem, and so the analytical solution method extending previous solution approaches is constructed.

UR - http://www.scopus.com/inward/record.url?scp=84856543265&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84856543265&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84856543265

SN - 9783540896180

VL - 58

T3 - Advances in Intelligent and Soft Computing

SP - 285

EP - 294

BT - Advances in Intelligent and Soft Computing

PB - Springer Verlag

ER -