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

電腦與通信工程研究所

研究成果: Paper › 同行評審

9 引文斯高帕斯（Scopus）

摘要

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.

原文	English
頁面	223-228
頁數	6
DOIs	https://doi.org/10.1109/IBICA.2012.8
出版狀態	Published - 2012 12月 12
事件	3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012 - Kaohsiung City, Taiwan 持續時間: 2012 9月 26 → 2012 9月 28

Other

Other	3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012
國家/地區	Taiwan
城市	Kaohsiung City
期間	12-09-26 → 12-09-28

All Science Journal Classification (ASJC) codes

生物工程
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10.1109/IBICA.2012.8

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title = "A hybrid PSO-based algorithm for solving DNA fragment assembly problem",

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.",

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

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day = "12",

doi = "10.1109/IBICA.2012.8",

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AU - Chen, Jui Le

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N2 - 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.

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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T2 - 3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012

Y2 - 26 September 2012 through 28 September 2012

ER -

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

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