Approximation of goal constraint coefficients in fuzzy goal programming

Nureize Arbaiy; Junzow Watada

doi:10.1109/ICCEA.2010.39

Approximation of goal constraint coefficients in fuzzy goal programming

Nureize Arbaiy^*, Junzow Watada

^*Corresponding author for this work

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

11 Citations (Scopus)

Abstract

It is sometimes difficult in real situations to estimate the coefficients of decision variables in multi-objective model. Even though mathematical analysis may contribute to determine these coefficients, historical data used may contain fuzzy and random properties and should be treated properly. Thus, this paper introduces a fuzzy random regression to approximate the coefficients; specifically the goal constraints of goal programming model. We propose a two phase-based approach for the solution model; first, we construct the goal constraints using fuzzy random regression model and, second, we solve the multi-objective problem with a fuzzy additive goal programming. A numerical example is presented to illustrate the model.

Original language	English
Title of host publication	2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010
Pages	161-165
Number of pages	5
Volume	1
DOIs	https://doi.org/10.1109/ICCEA.2010.39
Publication status	Published - 2010
Event	2nd International Conference on Computer Engineering and Applications, ICCEA 2010 - Duration: 2010 Mar 19 → 2010 Mar 21

Other

Other	2nd International Conference on Computer Engineering and Applications, ICCEA 2010
Period	10/3/19 → 10/3/21

Keywords

Coefficients
Fuzzy additive goal programming
Fuzzy random regression model
Goal constraints

ASJC Scopus subject areas

Computer Science Applications
Software

Access to Document

10.1109/ICCEA.2010.39

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title = "Approximation of goal constraint coefficients in fuzzy goal programming",

abstract = "It is sometimes difficult in real situations to estimate the coefficients of decision variables in multi-objective model. Even though mathematical analysis may contribute to determine these coefficients, historical data used may contain fuzzy and random properties and should be treated properly. Thus, this paper introduces a fuzzy random regression to approximate the coefficients; specifically the goal constraints of goal programming model. We propose a two phase-based approach for the solution model; first, we construct the goal constraints using fuzzy random regression model and, second, we solve the multi-objective problem with a fuzzy additive goal programming. A numerical example is presented to illustrate the model.",

keywords = "Coefficients, Fuzzy additive goal programming, Fuzzy random regression model, Goal constraints",

author = "Nureize Arbaiy and Junzow Watada",

year = "2010",

doi = "10.1109/ICCEA.2010.39",

language = "English",

isbn = "9780769539829",

volume = "1",

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note = "2nd International Conference on Computer Engineering and Applications, ICCEA 2010 ; Conference date: 19-03-2010 Through 21-03-2010",

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T1 - Approximation of goal constraint coefficients in fuzzy goal programming

AU - Arbaiy, Nureize

AU - Watada, Junzow

PY - 2010

Y1 - 2010

N2 - It is sometimes difficult in real situations to estimate the coefficients of decision variables in multi-objective model. Even though mathematical analysis may contribute to determine these coefficients, historical data used may contain fuzzy and random properties and should be treated properly. Thus, this paper introduces a fuzzy random regression to approximate the coefficients; specifically the goal constraints of goal programming model. We propose a two phase-based approach for the solution model; first, we construct the goal constraints using fuzzy random regression model and, second, we solve the multi-objective problem with a fuzzy additive goal programming. A numerical example is presented to illustrate the model.

AB - It is sometimes difficult in real situations to estimate the coefficients of decision variables in multi-objective model. Even though mathematical analysis may contribute to determine these coefficients, historical data used may contain fuzzy and random properties and should be treated properly. Thus, this paper introduces a fuzzy random regression to approximate the coefficients; specifically the goal constraints of goal programming model. We propose a two phase-based approach for the solution model; first, we construct the goal constraints using fuzzy random regression model and, second, we solve the multi-objective problem with a fuzzy additive goal programming. A numerical example is presented to illustrate the model.

KW - Coefficients

KW - Fuzzy additive goal programming

KW - Fuzzy random regression model

KW - Goal constraints

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U2 - 10.1109/ICCEA.2010.39

DO - 10.1109/ICCEA.2010.39

M3 - Conference contribution

AN - SCOPUS:77952662414

SN - 9780769539829

VL - 1

SP - 161

EP - 165

BT - 2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010

T2 - 2nd International Conference on Computer Engineering and Applications, ICCEA 2010

Y2 - 19 March 2010 through 21 March 2010

ER -

Approximation of goal constraint coefficients in fuzzy goal programming

Abstract

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Keywords

ASJC Scopus subject areas

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