The Application of an Improved Particle Swarm Optimization (PSO) Algorithm in Pairwise Sequence Alignment

In this paper, we applied an existing particle swarm optimization algorithm to biological pairwise sequence alignment problem. In addition, we improved the basic algorithm according to sequence characteristics. This improved algorithm provides constraint conditions of the initial position of particles and the mobile strategy in motion, taking account of the other particle swarm’ s next generation optimal value into the current ones. And the experiments shows that the improved algorithm have being reduced the possibility of being trapped into their own local optimization, enhanced the ability of scanning and improved the performance of the basic algorithm efficiently.

[1]  A. Cockshott,et al.  Improving the fermentation medium for Echinocandin B production part II: Particle swarm optimization , 2001 .

[2]  Christian Jacob,et al.  Exploratory Toolkit for Evolutionary and Swarm-Based Optimization , 2010 .

[3]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[4]  Ralf Bundschuh Rapid Significance Estimation in Local Sequence Alignment with Gaps , 2002, J. Comput. Biol..

[5]  F. Newagy,et al.  Designing near Shannon limit LDPC codes using particle swarm optimization algorithm , 2007, 2007 IEEE International Conference on Telecommunications and Malaysia International Conference on Communications.

[6]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[7]  T. Ray,et al.  A swarm with an effective information sharing mechanism for unconstrained and constrained single objective optimisation problems , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[8]  M. N. Vrahatis,et al.  Particle swarm optimization method in multiobjective problems , 2002, SAC '02.

[9]  Andries Petrus Engelbrecht,et al.  Cooperative learning in neural networks using particle swarm optimizers , 2000, South Afr. Comput. J..

[10]  Shang He,et al.  An improved particle swarm optimizer for mechanical design optimization problems , 2004 .

[11]  Author $article.title , 2002, Nature.

[12]  Qiang Zhao,et al.  Short communication Particle swarm optimization algorithm for partner selection in virtual enterprise , 2008 .

[13]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.