DocumentCode :
1922585
Title :
A Hybrid PSO-Based Algorithm for Solving DNA Fragment Assembly Problem
Author :
Huang, Ko-Wei ; Chen, Jui-Le ; Yang, Chu-Sing
Author_Institution :
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
fYear :
2012
fDate :
26-28 Sept. 2012
Firstpage :
223
Lastpage :
228
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.
Keywords :
DNA; biology; particle swarm optimisation; search problems; simulated annealing; DFA problem; DNA fragment assembly problem; SA algorithm-based local search; SPV rule; hybrid PSO-based algorithm; hybrid particle swarm optimization algorithm; overlapping-score measurement; simulated annealing algorithm-based local search; smallest position value rule; tabu search algorithms; Assembly; Benchmark testing; DNA; Doped fiber amplifiers; Heuristic algorithms; Particle swarm optimization; Simulated annealing; DNA; Fragment assembly problem; Particle swarm optimization; Smallest Position Value;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovations in Bio-Inspired Computing and Applications (IBICA), 2012 Third International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4673-2838-8
Type :
conf
DOI :
10.1109/IBICA.2012.8
Filename :
6337668
Link To Document :
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