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: | , , , , |
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| Format: | Article |
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Springer
2020
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| 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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| Summary: | 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. |
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