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Multi-Objective Linear Plus Linear Fractional Programming Problem based on Taylor Series Approximation

by Surapati Pramanik, Partha Pratim Dey, Bibhas C. Giri
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 32 - Number 8
Year of Publication: 2011
Authors: Surapati Pramanik, Partha Pratim Dey, Bibhas C. Giri
10.5120/3966-5589

Surapati Pramanik, Partha Pratim Dey, Bibhas C. Giri . Multi-Objective Linear Plus Linear Fractional Programming Problem based on Taylor Series Approximation. International Journal of Computer Applications. 32, 8 ( October 2011), 61-68. DOI=10.5120/3966-5589

@article{ 10.5120/3966-5589,
author = { Surapati Pramanik, Partha Pratim Dey, Bibhas C. Giri },
title = { Multi-Objective Linear Plus Linear Fractional Programming Problem based on Taylor Series Approximation },
journal = { International Journal of Computer Applications },
issue_date = { October 2011 },
volume = { 32 },
number = { 8 },
month = { October },
year = { 2011 },
issn = { 0975-8887 },
pages = { 61-68 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume32/number8/3966-5589/ },
doi = { 10.5120/3966-5589 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:18:42.048303+05:30
%A Surapati Pramanik
%A Partha Pratim Dey
%A Bibhas C. Giri
%T Multi-Objective Linear Plus Linear Fractional Programming Problem based on Taylor Series Approximation
%J International Journal of Computer Applications
%@ 0975-8887
%V 32
%N 8
%P 61-68
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper deals with fuzzy goal programming approach to multi-objective linear plus linear fractional programming problem based on Taylor series approximation. In the model formulation of the problem, we first construct the membership functions by determining individual optimal solutions of the objective functions subject to the system constraints. The membership functions are then transformed into equivalent linear membership functions by 1st order Taylor series approximation. Then fuzzy goal programming models are formulated in order to solve the problem by minimizing negative deviational variables. Euclidean distance function is then used to obtain compromise optimal solution. To demonstrate the efficiency and feasibility of the proposed approach, two numerical examples are solved and compared with existing methods in the literature.

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Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy programming Fuzzy goal programming Linear Fractional programming Multi-objective linear plus linear fractional programming Taylor series

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