Fuzzy goal programming applied to multi-objective programming problem with FREs as constraints

This paper presents an alternate technique based on fuzzy goal programming (FGP) approach to solve multi-objective programming problem with fuzzy relational equations (FREs) as constraints. The proposed technique is more efficient and requires less computational work than that of algorithm suggested...

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Main Author: Kailash Lachhwani
Format: Article
Language:English
Published: Growing Science 2015-09-01
Series:Decision Science Letters
Subjects:
Online Access:http://www.growingscience.com/dsl/Vol4/dsl_2015_29.pdf
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spelling doaj-6ce9a57ca8424863a96f3a549e5d9b262020-11-25T00:44:58ZengGrowing ScienceDecision Science Letters1929-58041929-58122015-09-014446547610.5267/j.dsl.2015.6.003Fuzzy goal programming applied to multi-objective programming problem with FREs as constraintsKailash Lachhwani This paper presents an alternate technique based on fuzzy goal programming (FGP) approach to solve multi-objective programming problem with fuzzy relational equations (FREs) as constraints. The proposed technique is more efficient and requires less computational work than that of algorithm suggested by Jain and Lachhwani (2009) [Jain, & Lachhwani (2009). Multiobjective programming problem with fuzzy relational equations. International Journal of Operations Research, 6(2), 5563.]. In FGP formulation, objectives are transformed into the fuzzy goals using maximum and minimal solutions elements of FREs feasible solution set. A pseudo code computer algorithm is developed for computation of maximum solution of FREs. Suitable linear membership function is defined for each objective function. Then achievement of the highest membership value of each of the fuzzy goals is formulated by minimizing the sum of negative deviational variables. The aim of this paper is to present a simple and efficient solution procedure to obtain compromise optimal solution of multiobjective optimization problem with FREs as constraints. A comparative analysis is also carried out between two methodologies based on numerical examples.http://www.growingscience.com/dsl/Vol4/dsl_2015_29.pdfFuzzy relational equationsMinimal solutionCompromise optimal solutionFuzzy goal programming
collection DOAJ
language English
format Article
sources DOAJ
author Kailash Lachhwani
spellingShingle Kailash Lachhwani
Fuzzy goal programming applied to multi-objective programming problem with FREs as constraints
Decision Science Letters
Fuzzy relational equations
Minimal solution
Compromise optimal solution
Fuzzy goal programming
author_facet Kailash Lachhwani
author_sort Kailash Lachhwani
title Fuzzy goal programming applied to multi-objective programming problem with FREs as constraints
title_short Fuzzy goal programming applied to multi-objective programming problem with FREs as constraints
title_full Fuzzy goal programming applied to multi-objective programming problem with FREs as constraints
title_fullStr Fuzzy goal programming applied to multi-objective programming problem with FREs as constraints
title_full_unstemmed Fuzzy goal programming applied to multi-objective programming problem with FREs as constraints
title_sort fuzzy goal programming applied to multi-objective programming problem with fres as constraints
publisher Growing Science
series Decision Science Letters
issn 1929-5804
1929-5812
publishDate 2015-09-01
description This paper presents an alternate technique based on fuzzy goal programming (FGP) approach to solve multi-objective programming problem with fuzzy relational equations (FREs) as constraints. The proposed technique is more efficient and requires less computational work than that of algorithm suggested by Jain and Lachhwani (2009) [Jain, & Lachhwani (2009). Multiobjective programming problem with fuzzy relational equations. International Journal of Operations Research, 6(2), 5563.]. In FGP formulation, objectives are transformed into the fuzzy goals using maximum and minimal solutions elements of FREs feasible solution set. A pseudo code computer algorithm is developed for computation of maximum solution of FREs. Suitable linear membership function is defined for each objective function. Then achievement of the highest membership value of each of the fuzzy goals is formulated by minimizing the sum of negative deviational variables. The aim of this paper is to present a simple and efficient solution procedure to obtain compromise optimal solution of multiobjective optimization problem with FREs as constraints. A comparative analysis is also carried out between two methodologies based on numerical examples.
topic Fuzzy relational equations
Minimal solution
Compromise optimal solution
Fuzzy goal programming
url http://www.growingscience.com/dsl/Vol4/dsl_2015_29.pdf
work_keys_str_mv AT kailashlachhwani fuzzygoalprogrammingappliedtomultiobjectiveprogrammingproblemwithfresasconstraints
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