• 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