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Multi-Objective Fuzzy Chance Constrained Fuzzy Goal Programming for Capacitated Transportation Problem

by A.k. Bhargava, S.r. Singh, Divya Bansal
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 107 - Number 3
Year of Publication: 2014
Authors: A.k. Bhargava, S.r. Singh, Divya Bansal
10.5120/18732-9971

A.k. Bhargava, S.r. Singh, Divya Bansal . Multi-Objective Fuzzy Chance Constrained Fuzzy Goal Programming for Capacitated Transportation Problem. International Journal of Computer Applications. 107, 3 ( December 2014), 18-23. DOI=10.5120/18732-9971

@article{ 10.5120/18732-9971,
author = { A.k. Bhargava, S.r. Singh, Divya Bansal },
title = { Multi-Objective Fuzzy Chance Constrained Fuzzy Goal Programming for Capacitated Transportation Problem },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 107 },
number = { 3 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 18-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume107/number3/18732-9971/ },
doi = { 10.5120/18732-9971 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:40:06.040835+05:30
%A A.k. Bhargava
%A S.r. Singh
%A Divya Bansal
%T Multi-Objective Fuzzy Chance Constrained Fuzzy Goal Programming for Capacitated Transportation Problem
%J International Journal of Computer Applications
%@ 0975-8887
%V 107
%N 3
%P 18-23
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a multi-objective fuzzy chance constrained capacitated transportation problem based on fuzzy goal programming problem with capacity restrictions on commodities which are shipped from different sources to different destinations. The capacity of each origin and the demand of each destination are considered random in nature with fuzzy normal stochastic parameters following normal distribution with fuzzy mean and fuzzy variance respectively. These inequality constraints are also considered as fuzzy probabilistic in nature assuming to be triangular fuzzy numbers. Further, the supply and demand constraints are converted into equivalent deterministic forms. Then, we define the fuzzy goal tolerance limit of each of the objective functions which are then characterized by the associated membership functions. In the solution process, the fuzzy parameters are defuzzied by applying graded mean integration method which provided a satisfactory result. Further, an illustrative example is solved to demonstrate the effectiveness of the proposed model.

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Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy goal programming fuzzy chance constrained programming capacitated transportation problem multi objective decision making graded mean integration method.

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