Building multi-objective fuzzy random programming model

Nureize Arbaiy; Junzo Watada

doi:10.1109/FUZZ-IEEE.2013.6622575

Building multi-objective fuzzy random programming model

Nureize Arbaiy, Junzo Watada

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

1 Citation (Scopus)

Abstract

A real-life application faces various kinds of inherent uncertainties which occurs simultaneously. To find solution, formulating real world problem into mathematical programming model is challenging. Uncertain parameters in a problem model can be characterized as vagueness, ambiguous and random of the information. Such uncertainties make the existing multi-objective model incapable of handling such situations. Thus, in this paper we present the multi-objective decision model from the perspective of possibilistic programming approach to scrutinize the uncertainties in the decision making. The proposed concept can be used to build model for multi-objective problem which is exposed with various types of uncertainties. We include an illustrative example to explain the model, and highlight its advantages.

Original language	English
Title of host publication	IEEE International Conference on Fuzzy Systems
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2013.6622575
Publication status	Published - 2013
Event	2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013 - Hyderabad Duration: 2013 Jul 7 → 2013 Jul 10

Other

Other	2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013
City	Hyderabad
Period	13/7/7 → 13/7/10

Keywords

Fuzzy random coefficient
Multi-objective evaluation
Necessity measure
Possibilistic programming

ASJC Scopus subject areas

Software
Artificial Intelligence
Applied Mathematics
Theoretical Computer Science

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10.1109/FUZZ-IEEE.2013.6622575

Cite this

@inproceedings{3a77b09d02504b618485c2d95b698728,

title = "Building multi-objective fuzzy random programming model",

abstract = "A real-life application faces various kinds of inherent uncertainties which occurs simultaneously. To find solution, formulating real world problem into mathematical programming model is challenging. Uncertain parameters in a problem model can be characterized as vagueness, ambiguous and random of the information. Such uncertainties make the existing multi-objective model incapable of handling such situations. Thus, in this paper we present the multi-objective decision model from the perspective of possibilistic programming approach to scrutinize the uncertainties in the decision making. The proposed concept can be used to build model for multi-objective problem which is exposed with various types of uncertainties. We include an illustrative example to explain the model, and highlight its advantages.",

keywords = "Fuzzy random coefficient, Multi-objective evaluation, Necessity measure, Possibilistic programming",

author = "Nureize Arbaiy and Junzo Watada",

year = "2013",

doi = "10.1109/FUZZ-IEEE.2013.6622575",

language = "English",

isbn = "9781479900220",

booktitle = "IEEE International Conference on Fuzzy Systems",

note = "2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013 ; Conference date: 07-07-2013 Through 10-07-2013",

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TY - GEN

T1 - Building multi-objective fuzzy random programming model

AU - Arbaiy, Nureize

AU - Watada, Junzo

PY - 2013

Y1 - 2013

N2 - A real-life application faces various kinds of inherent uncertainties which occurs simultaneously. To find solution, formulating real world problem into mathematical programming model is challenging. Uncertain parameters in a problem model can be characterized as vagueness, ambiguous and random of the information. Such uncertainties make the existing multi-objective model incapable of handling such situations. Thus, in this paper we present the multi-objective decision model from the perspective of possibilistic programming approach to scrutinize the uncertainties in the decision making. The proposed concept can be used to build model for multi-objective problem which is exposed with various types of uncertainties. We include an illustrative example to explain the model, and highlight its advantages.

AB - A real-life application faces various kinds of inherent uncertainties which occurs simultaneously. To find solution, formulating real world problem into mathematical programming model is challenging. Uncertain parameters in a problem model can be characterized as vagueness, ambiguous and random of the information. Such uncertainties make the existing multi-objective model incapable of handling such situations. Thus, in this paper we present the multi-objective decision model from the perspective of possibilistic programming approach to scrutinize the uncertainties in the decision making. The proposed concept can be used to build model for multi-objective problem which is exposed with various types of uncertainties. We include an illustrative example to explain the model, and highlight its advantages.

KW - Fuzzy random coefficient

KW - Multi-objective evaluation

KW - Necessity measure

KW - Possibilistic programming

UR - http://www.scopus.com/inward/record.url?scp=84887846727&partnerID=8YFLogxK

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U2 - 10.1109/FUZZ-IEEE.2013.6622575

DO - 10.1109/FUZZ-IEEE.2013.6622575

M3 - Conference contribution

AN - SCOPUS:84887846727

SN - 9781479900220

BT - IEEE International Conference on Fuzzy Systems

T2 - 2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013

Y2 - 7 July 2013 through 10 July 2013

ER -

Building multi-objective fuzzy random programming model

Abstract

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Keywords

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