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Dinkelbach Approach for Solving Interval-valued Multiobjective Fractional Programming Problems using Goal Programming

by Mousumi Kumar, Bijay Baran Pal
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 57 - Number 8
Year of Publication: 2012
Authors: Mousumi Kumar, Bijay Baran Pal
10.5120/9133-3321

Mousumi Kumar, Bijay Baran Pal . Dinkelbach Approach for Solving Interval-valued Multiobjective Fractional Programming Problems using Goal Programming. International Journal of Computer Applications. 57, 8 ( November 2012), 12-17. DOI=10.5120/9133-3321

@article{ 10.5120/9133-3321,
author = { Mousumi Kumar, Bijay Baran Pal },
title = { Dinkelbach Approach for Solving Interval-valued Multiobjective Fractional Programming Problems using Goal Programming },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 57 },
number = { 8 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 12-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume57/number8/9133-3321/ },
doi = { 10.5120/9133-3321 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:59:53.547938+05:30
%A Mousumi Kumar
%A Bijay Baran Pal
%T Dinkelbach Approach for Solving Interval-valued Multiobjective Fractional Programming Problems using Goal Programming
%J International Journal of Computer Applications
%@ 0975-8887
%V 57
%N 8
%P 12-17
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents an interval valued goal programming approach for solving multiobjective fractional programming problems. In the model formulation of the problem, the interval-valued system constraints are converted in to equivalent crisp system. The interval valued fractional objective goals are transformed into linear goals by employing the iterative parametric method which is an extension of Dinkelbach approach. In the solution process, the goal achievement function, termed as 'regret function', is formulated for minimizing the unwanted deviational variables to achieve the goals in their specified ranges and thereby arriving at most satisfactory solution in the decision making environment. To illustrate the proposed approach one numerical example is solved.

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Index Terms

Computer Science
Information Sciences

Keywords

Dinkelbach approach Fractional Programming Goal Programming Interval Arithmetic Interval Programming

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