A hybrid PSO-based algorithm for solving DNA fragment assembly problem

Ko Wei Huang; Jui Le Chen; Chu Sing Yang

doi:10.1109/IBICA.2012.8

A hybrid PSO-based algorithm for solving DNA fragment assembly problem

Ko Wei Huang, Jui Le Chen, Chu Sing Yang

Institute of Computer and Communication Engineering

Research output: Contribution to conference › Paper › peer-review

9 Citations (Scopus)

Abstract

In this paper, a hybrid particle swarm optimization algorithm (HPSO) is proposed for the DNA fragment assembly (DFA) problem by maximizing the overlapping-score measurement. The smallest position value (SPV) rule is used for encoding the particles to enable PSO to be suitable for DFA, and the Tabu search algorithms are used to initialize the particles. Additionally, a simulated annealing (SA) algorithm-based local search is utilized for local search to improve the best solution after the PSO search process. Finally, the results show that HPSO can significantly get better overlap score than other PSO-based algorithms with different-sized benchmarks.

Original language	English
Pages	223-228
Number of pages	6
DOIs	https://doi.org/10.1109/IBICA.2012.8
Publication status	Published - 2012 Dec 12
Event	3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012 - Kaohsiung City, Taiwan Duration: 2012 Sept 26 → 2012 Sept 28

Other

Other	3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012
Country/Territory	Taiwan
City	Kaohsiung City
Period	12-09-26 → 12-09-28

All Science Journal Classification (ASJC) codes

Bioengineering
Software

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10.1109/IBICA.2012.8

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author = "Huang, {Ko Wei} and Chen, {Jui Le} and Yang, {Chu Sing}",

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AB - In this paper, a hybrid particle swarm optimization algorithm (HPSO) is proposed for the DNA fragment assembly (DFA) problem by maximizing the overlapping-score measurement. The smallest position value (SPV) rule is used for encoding the particles to enable PSO to be suitable for DFA, and the Tabu search algorithms are used to initialize the particles. Additionally, a simulated annealing (SA) algorithm-based local search is utilized for local search to improve the best solution after the PSO search process. Finally, the results show that HPSO can significantly get better overlap score than other PSO-based algorithms with different-sized benchmarks.

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A hybrid PSO-based algorithm for solving DNA fragment assembly problem

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