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Reseach Article

A Fast Algorithm for Finding the Non Dominated Set in Multi objective Optimization

by K.K.Mishra, Sandeep Harit
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 25
Year of Publication: 2010
Authors: K.K.Mishra, Sandeep Harit
10.5120/460-764

K.K.Mishra, Sandeep Harit . A Fast Algorithm for Finding the Non Dominated Set in Multi objective Optimization. International Journal of Computer Applications. 1, 25 ( February 2010), 35-39. DOI=10.5120/460-764

@article{ 10.5120/460-764,
author = { K.K.Mishra, Sandeep Harit },
title = { A Fast Algorithm for Finding the Non Dominated Set in Multi objective Optimization },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 25 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 35-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number25/460-764/ },
doi = { 10.5120/460-764 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:48:32.704730+05:30
%A K.K.Mishra
%A Sandeep Harit
%T A Fast Algorithm for Finding the Non Dominated Set in Multi objective Optimization
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 25
%P 35-39
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The working of single objective optimization algorithm and multi objective optimization algorithm is quite different. This difference is due to number of optimal solution approached by both the algorithms. In single objective optimization problem there will be a single optimal solution, even though in multi model optimization there may be more than one solution but we are interested in only one optimal solution, where as in multi objective optimization problem, there will be many set of optimal solutions. These sets are called different non dominated front, and every non dominated front will contain a set of non dominated solutions thus there are two tasks of an ideal multi objective optimization algorithm (i) To find multiple non dominated fronts (or to identify different set of non dominated solutions). (ii) To seek for Pareto optimal solutions with a good diversity in objective and decision variable values.

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Index Terms

Computer Science
Information Sciences

Keywords

FAST ALGORITHM MULTIOBJECTIVE OPTIMIZATION