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Adaptive Mutation Dynamic Search Fireworks Algorithm

School of Computer, Shenyang Aerospace University, Shenyang 110136, China
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Academic Editor: Pierre Leone
Algorithms 2017, 10(2), 48; https://doi.org/10.3390/a10020048
Received: 23 February 2017 / Revised: 20 April 2017 / Accepted: 25 April 2017 / Published: 28 April 2017
The Dynamic Search Fireworks Algorithm (dynFWA) is an effective algorithm for solving optimization problems. However, dynFWA easily falls into local optimal solutions prematurely and it also has a slow convergence rate. In order to improve these problems, an adaptive mutation dynamic search fireworks algorithm (AMdynFWA) is introduced in this paper. The proposed algorithm applies the Gaussian mutation or the Levy mutation for the core firework (CF) with mutation probability. Our simulation compares the proposed algorithm with the FWA-Based algorithms and other swarm intelligence algorithms. The results show that the proposed algorithm achieves better overall performance on the standard test functions. View Full-Text
Keywords: dynamic search fireworks algorithm; Gaussian mutation; Levy mutation; mutation probability; standard test functions dynamic search fireworks algorithm; Gaussian mutation; Levy mutation; mutation probability; standard test functions
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Li, X.-G.; Han, S.-F.; Zhao, L.; Gong, C.-Q.; Liu, X.-J. Adaptive Mutation Dynamic Search Fireworks Algorithm. Algorithms 2017, 10, 48.

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