@article{scholars13866,
           pages = {121--140},
         journal = {Studies in Systems, Decision and Control},
       publisher = {Springer},
            year = {2020},
           title = {Hybrid ABFA-APSO Algorithm},
             doi = {10.1007/978-3-030-47737-0{$_5$}},
          volume = {293},
            note = {cited By 8},
        abstract = {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. {\^A}{\copyright} 2020, Springer Nature Switzerland AG.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085220140&doi=10.1007\%2f978-3-030-47737-0\%5f5&partnerID=40&md5=3caee760e8a0a4d29eddc6cba19a1bc5},
            issn = {21984182},
          author = {Hassan, S. M. and Ibrahim, R. and Saad, N. and Bingi, K. and Asirvadam, V. S.}
}