Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem

Bat algorithm lags behind other modern metaheuristic algorithms in terms of search efficiency, due to premature convergence. Once trapped in any sub-optimal region, the algorithm is unable to escape because of deficiency in population diversity. To address this, an enhanced Bat Algorithm (EBA) is in...

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Main Authors: Hussain, K., Zhu, W., Salleh, M.N.M., Ali, H., Talpur, N., Naseem, R., Ahmad, A., Ullah, A.
Format: Article
Published: Springer 2020
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078430728&doi=10.1007%2f978-3-030-36056-6_39&partnerID=40&md5=b98e2c48250e3798b76e065b1b019f39
http://eprints.utp.edu.my/24740/
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spelling my.utp.eprints.247402021-08-27T05:51:12Z Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem Hussain, K. Zhu, W. Salleh, M.N.M. Ali, H. Talpur, N. Naseem, R. Ahmad, A. Ullah, A. Bat algorithm lags behind other modern metaheuristic algorithms in terms of search efficiency, due to premature convergence. Once trapped in any sub-optimal region, the algorithm is unable to escape because of deficiency in population diversity. To address this, an enhanced Bat Algorithm (EBA) is introduced in this paper. The EBA algorithm comes with adaptive exploration and exploitation capability, as well as, additional population diversity. This enables EBA improve its convergence ability to find even better solutions towards the end of search process, where standard BA is often trapped. To illustrate effectiveness of the proposed method, EBA is applied on non-linear, non-convex economic dispatch problem with a power generation system comprising of twenty thermal units. The experimental results suggest that EBA not only saved power generation cost but also reduced transmission losses, more efficiently as compared to original BA and other methods reported in literature. The EBA algorithm also showed enhanced convergence ability than BA towards the end of iterations. © Springer Nature Switzerland AG 2020. Springer 2020 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078430728&doi=10.1007%2f978-3-030-36056-6_39&partnerID=40&md5=b98e2c48250e3798b76e065b1b019f39 Hussain, K. and Zhu, W. and Salleh, M.N.M. and Ali, H. and Talpur, N. and Naseem, R. and Ahmad, A. and Ullah, A. (2020) Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem. Advances in Intelligent Systems and Computing, 978 AI . pp. 419-428. http://eprints.utp.edu.my/24740/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Bat algorithm lags behind other modern metaheuristic algorithms in terms of search efficiency, due to premature convergence. Once trapped in any sub-optimal region, the algorithm is unable to escape because of deficiency in population diversity. To address this, an enhanced Bat Algorithm (EBA) is introduced in this paper. The EBA algorithm comes with adaptive exploration and exploitation capability, as well as, additional population diversity. This enables EBA improve its convergence ability to find even better solutions towards the end of search process, where standard BA is often trapped. To illustrate effectiveness of the proposed method, EBA is applied on non-linear, non-convex economic dispatch problem with a power generation system comprising of twenty thermal units. The experimental results suggest that EBA not only saved power generation cost but also reduced transmission losses, more efficiently as compared to original BA and other methods reported in literature. The EBA algorithm also showed enhanced convergence ability than BA towards the end of iterations. © Springer Nature Switzerland AG 2020.
format Article
author Hussain, K.
Zhu, W.
Salleh, M.N.M.
Ali, H.
Talpur, N.
Naseem, R.
Ahmad, A.
Ullah, A.
spellingShingle Hussain, K.
Zhu, W.
Salleh, M.N.M.
Ali, H.
Talpur, N.
Naseem, R.
Ahmad, A.
Ullah, A.
Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem
author_facet Hussain, K.
Zhu, W.
Salleh, M.N.M.
Ali, H.
Talpur, N.
Naseem, R.
Ahmad, A.
Ullah, A.
author_sort Hussain, K.
title Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem
title_short Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem
title_full Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem
title_fullStr Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem
title_full_unstemmed Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem
title_sort enhanced bat algorithm for solving non-convex economic dispatch problem
publisher Springer
publishDate 2020
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078430728&doi=10.1007%2f978-3-030-36056-6_39&partnerID=40&md5=b98e2c48250e3798b76e065b1b019f39
http://eprints.utp.edu.my/24740/
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