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计算机工程 ›› 2011, Vol. 37 ›› Issue (3): 10-12. doi: 10.3969/j.issn.1000-3428.2011.03.004

• 博士论文 • 上一篇    下一篇

基于文化微粒群优化算法的DNA编码研究

殷 脂1,2,叶春明1,温 蜜2   

  1. (1. 上海理工大学管理学院,上海 200093;2. 上海电力学院计算机信息工程学院,上海 200090)
  • 出版日期:2011-02-05 发布日期:2011-01-28
  • 作者简介:殷 脂(1981-),女, 讲师、博士研究生,主研方向:智能优化,人工智能;叶春明,教授、博士生导师;温 蜜,讲师、博士
  • 基金资助:
    国家自然科学基金资助项目(60903188);上海市高校选拔培养优秀青年教师科研专项基金资助项目(sdl-07013);高等学校博士点基金资助项目(20093120110008);上海市重点学科建设基金资助项目(S30504)

Research on DNA Encoding Based on Cultural Particle Swarm Optimization Algorithm

YIN Zhi 1,2, YE Chun-ming 1, WEN Mi 2   

  1. (1. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China; 2. School of Computer and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China)
  • Online:2011-02-05 Published:2011-01-28

摘要: 对DNA编码约束进行研究,选择汉明测量以及相似度作为DNA序列集设计的主要约束,并结合连续性约束与GC Content约束,将序列集设计问题抽象为带有强约束的多目标优化问题,采用文化微粒群算法解决该多目标优化问题。仿真结果表明,该混合算法针对DNA编码序列设计问题,在求解最优值能力、解的稳定性方面都能取得较好的效果。

关键词: 微粒群优化算法, 文化演化, DNA编码, 汉明测量

Abstract: DNA encoding constrained is researched. H-measure and similarity is the principal constrained for DNA sequence design. Continuity and GC Content is also another constrained. DNA sequence design is presented to solve the multi-objective optimization problem. Particle Swarm Optimization based on Cultural Algorithm(PSO-CA) is proposed to solve the DNA sequence design as a multi-objective optimization problem. Simulation results indicate the hybrid algorithm does well on searching efficiency and key stability for DNA sequence design problem.

Key words: Particle Swarm Optimization(PSO) algorithm, cultural evolution, DNA encoding, H-measure

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