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Reseach Article

Oppositional Biogeography-Based Optimization for Solving Economic Dispatch Problems: An Efficient Method

Published on March 2014 by Parmar K.P.Singh, Bhuvnesh Khokhar
International Conference on Advances in Computer Engineering and Applications
Foundation of Computer Science USA
ICACEA - Number 2
March 2014
Authors: Parmar K.P.Singh, Bhuvnesh Khokhar
115b6168-e979-4e31-a020-c76557afce70

Parmar K.P.Singh, Bhuvnesh Khokhar . Oppositional Biogeography-Based Optimization for Solving Economic Dispatch Problems: An Efficient Method. International Conference on Advances in Computer Engineering and Applications. ICACEA, 2 (March 2014), 53-58.

@article{
author = { Parmar K.P.Singh, Bhuvnesh Khokhar },
title = { Oppositional Biogeography-Based Optimization for Solving Economic Dispatch Problems: An Efficient Method },
journal = { International Conference on Advances in Computer Engineering and Applications },
issue_date = { March 2014 },
volume = { ICACEA },
number = { 2 },
month = { March },
year = { 2014 },
issn = 0975-8887,
pages = { 53-58 },
numpages = 6,
url = { /proceedings/icacea/number2/15622-1417/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Computer Engineering and Applications
%A Parmar K.P.Singh
%A Bhuvnesh Khokhar
%T Oppositional Biogeography-Based Optimization for Solving Economic Dispatch Problems: An Efficient Method
%J International Conference on Advances in Computer Engineering and Applications
%@ 0975-8887
%V ICACEA
%N 2
%P 53-58
%D 2014
%I International Journal of Computer Applications
Abstract

In this paper, Oppositional biogeography-based optimization (OBBO) technique based on opposition-based learning (OBL) concept has been presented for solving the economic dispatch (ED) problems. The OBBO technique has been applied on two test systems, one consisting of three generators and the other of six generators. The results obtained have been compared with the conventional Lagrange multiplier method, particle swarm optimization (PSO) and biogeography-based optimization (BBO) methods. The results show that the presented OBBO technique has good convergence characteristics and provides comparatively better solutions in terms of total fuel cost as compared to other methods. Also, the global search capability is enhanced and premature convergence is avoided.

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Index Terms

Computer Science
Information Sciences

Keywords

Biogeography-Based Optimization Economic Dispatch Oppositional Biogeography-Based Optimization Opposition- Based Learning