Application of disturbance of DNA fragments in swarm intelligence algorithm

Yanmin Liu, Ben Niu, Tung Sun Chan, Rui Liu, Sui changling

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


Optimization problem is one of the most important problems encountered in the real world. In order to effectively deal with optimization problem, some intelligence algorithms have been put forward, for example, PSO, GA, etc. To effectively solve this kind of problem, in this paper, crossing strategy of DNA fragments is proposed to explore the effect on intelligence algorithms based on American genetic biologist Morgan theory. We mainly focus on DNA fragment decreasing strategy and DNA fragment increasing strategy based on disturbance in PSO. In order to test the role of the DNA mechanism, three test benchmarks were selected to conduct the analysis of convergence property and statistical property. The simulation results show that the PSO with DNA mechanism have an advantage on algorithm performance efficiency compared with the original proposed PSO. Therefore, DNA mechanism is an effective method for improving swarm Intelligence algorithm performance.
Original languageEnglish
Title of host publicationIntelligent Computing Theories and Methodologies - 11th International Conference, ICIC 2015, Proceedings
PublisherSpringer Verlag
Number of pages9
ISBN (Print)9783319221854
Publication statusPublished - 1 Jan 2015
Event11th International Conference on Intelligent Computing, ICIC 2015 - Fuzhou, China
Duration: 20 Aug 201523 Aug 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on Intelligent Computing, ICIC 2015


  • Algorithm
  • DNA fragments
  • Swarm intelligence

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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