Chaos inspired Particle Swarm Optimization with Levy Flight for Genome
Sequence Assembly
- URL: http://arxiv.org/abs/2110.10623v1
- Date: Wed, 20 Oct 2021 15:24:27 GMT
- Title: Chaos inspired Particle Swarm Optimization with Levy Flight for Genome
Sequence Assembly
- Authors: Sehej Jain and Kusum Kumari Bharti
- Abstract summary: In this paper, we propose a new variant of PSO to address the permutation-optimization problem.
PSO is integrated with the Chaos and Levy Flight (A random walk algorithm) to effectively balance the exploration and exploitation capability of the algorithm.
Empirical experiments are conducted to evaluate the performance of the proposed method in comparison to the other variants of PSO proposed in the literature.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: With the advent of Genome Sequencing, the field of Personalized Medicine has
been revolutionized. From drug testing and studying diseases and mutations to
clan genomics, studying the genome is required. However, genome sequence
assembly is a very complex combinatorial optimization problem of computational
biology. PSO is a popular meta-heuristic swarm intelligence optimization
algorithm, used to solve combinatorial optimization problems. In this paper, we
propose a new variant of PSO to address this permutation-optimization problem.
PSO is integrated with the Chaos and Levy Flight (A random walk algorithm) to
effectively balance the exploration and exploitation capability of the
algorithm. Empirical experiments are conducted to evaluate the performance of
the proposed method in comparison to the other variants of the PSO proposed in
the literature. The analysis is conducted on four DNA coverage datasets. The
conducted analysis demonstrates that the proposed model attain a better
performance with better reliability and consistency in comparison to other
competitive methods in all cases.
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