An Improved Artificial Fish Swarm Algorithm and Its Application in Multiple Sequence Alignment
In this paper, a hybrid optimization algorithm for the Multiple Sequence Alignment is presented. Our method is presented Artificial Fish Swarm Algorithm by employing some improvements. The goal of our method is to reduce the required computing time and get better solution. In our simulations
we use the instances of TSPLIB to show that the speed of convergence of the improved algorithm can be enhanced greatly compared with the traditional algorithm, we also present the comparison of the improved algorithm and the traditional algorithm on different sequences.
Document Type: Research Article
Publication date: 01 March 2014
- Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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