Hybrid ABFA-APSO Algorithm

The aim of this chapter is to propose improvement to the adaptation of bacterial foraging algorithm (BFA) and to hybridize it with accelerated particle swarm optimization (APSO) in order to accelerate its convergence. In the proposed algorithm, the random walk in the chemotaxis stage of the ABFA is...

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Main Authors: Hassan, S.M., Ibrahim, R., Saad, N., Bingi, K., Asirvadam, V.S.
Format: Article
Published: Springer 2020
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085220140&doi=10.1007%2f978-3-030-47737-0_5&partnerID=40&md5=3caee760e8a0a4d29eddc6cba19a1bc5
http://eprints.utp.edu.my/24787/
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spelling my.utp.eprints.247872021-08-27T06:27:05Z Hybrid ABFA-APSO Algorithm Hassan, S.M. Ibrahim, R. Saad, N. Bingi, K. Asirvadam, V.S. The aim of this chapter is to propose improvement to the adaptation of bacterial foraging algorithm (BFA) and to hybridize it with accelerated particle swarm optimization (APSO) in order to accelerate its convergence. In the proposed algorithm, the random walk in the chemotaxis stage of the ABFA is updated through the velocity equation of the APSO. © 2020, Springer Nature Switzerland AG. Springer 2020 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085220140&doi=10.1007%2f978-3-030-47737-0_5&partnerID=40&md5=3caee760e8a0a4d29eddc6cba19a1bc5 Hassan, S.M. and Ibrahim, R. and Saad, N. and Bingi, K. and Asirvadam, V.S. (2020) Hybrid ABFA-APSO Algorithm. Studies in Systems, Decision and Control, 293 . pp. 121-140. http://eprints.utp.edu.my/24787/
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 The aim of this chapter is to propose improvement to the adaptation of bacterial foraging algorithm (BFA) and to hybridize it with accelerated particle swarm optimization (APSO) in order to accelerate its convergence. In the proposed algorithm, the random walk in the chemotaxis stage of the ABFA is updated through the velocity equation of the APSO. © 2020, Springer Nature Switzerland AG.
format Article
author Hassan, S.M.
Ibrahim, R.
Saad, N.
Bingi, K.
Asirvadam, V.S.
spellingShingle Hassan, S.M.
Ibrahim, R.
Saad, N.
Bingi, K.
Asirvadam, V.S.
Hybrid ABFA-APSO Algorithm
author_facet Hassan, S.M.
Ibrahim, R.
Saad, N.
Bingi, K.
Asirvadam, V.S.
author_sort Hassan, S.M.
title Hybrid ABFA-APSO Algorithm
title_short Hybrid ABFA-APSO Algorithm
title_full Hybrid ABFA-APSO Algorithm
title_fullStr Hybrid ABFA-APSO Algorithm
title_full_unstemmed Hybrid ABFA-APSO Algorithm
title_sort hybrid abfa-apso algorithm
publisher Springer
publishDate 2020
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085220140&doi=10.1007%2f978-3-030-47737-0_5&partnerID=40&md5=3caee760e8a0a4d29eddc6cba19a1bc5
http://eprints.utp.edu.my/24787/
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