Abstract
In this paper, an improved interior search algorithm (ISA) is designed by incorporating \(L\acute{e}vy\) flight for solving optimisation problems. \(L\acute{e}vy\) flight pattern seen in some birds, is a special type of movement along a straight line followed by sudden turns in random directions. The convergence rate of ISA is improved using the principles of \(L\acute{e}vy\) flight in the proposed levy interior search algorithm (LISA). LISA is validated against a set of benchmark optimisation problems to demonstrate its performance. Further, LISA is used for parameter identification of an integer order Rossler’s chaotic system. Simulation results show that LISA outperforms other well-known existing optimisation algorithms like particle swarm optimisation (PSO), ISA and cuckoo search algorithm (CSA).
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Acknowledgments
This work was supported by the Department of Science and Technology, Government of India under the INSPIRE Faculty Award Scheme (IFA-13 ENG-45).
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Jariwala, R., Patidar, R., George, N.V. (2015). A Levy Interior Search Algorithm for Chaotic System Identification. In: Matoušek, R. (eds) Mendel 2015. ICSC-MENDEL 2016. Advances in Intelligent Systems and Computing, vol 378. Springer, Cham. https://doi.org/10.1007/978-3-319-19824-8_11
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DOI: https://doi.org/10.1007/978-3-319-19824-8_11
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