Biogeography-based optimization with improved migration operator and self-adaptive clear duplicate operator View Full Text


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Article Info

DATE

2014-09

AUTHORS

Quanxi Feng, Sanyang Liu, Jianke Zhang, Guoping Yang, Longquan Yong

ABSTRACT

Biogeography-based optimization (BBO) is a new emerging population-based algorithm that has been shown to be competitive with other evolutionary algorithms. However, there are some insufficiencies in solving complex problems, such as poor population diversity and slow convergence speed in the later stage. To overcome these shortcomings, we propose an improved BBO (IBBO) algorithm integrating a new improved migration operator, Gaussian mutation operator, and self-adaptive clear duplicate operator. The improved migration operator simultaneously adopts more information from other habitats, maintains population diversity, and preserves exploitation ability. The self-adaptive clear duplicate operator can clear duplicate or almost identical habitats, while also preserving population diversity through a self-adaptation threshold within the evolution process. Simulation results and comparisons from the experimental tests conducted on 23 benchmark functions show that IBBO achieves excellent performance in solving complex problems compared with other variants of the BBO algorithm and other evolutionary algorithms. The performance of the improved migration operator is also discussed. More... »

PAGES

563-581

References to SciGraph publications

  • 2013-04. Dynamic clustering using combinatorial particle swarm optimization in APPLIED INTELLIGENCE
  • 2013-07. Block-matching algorithm based on harmony search optimization for motion estimation in APPLIED INTELLIGENCE
  • 2012-10. A multi-threshold segmentation approach based on Artificial Bee Colony optimization in APPLIED INTELLIGENCE
  • 2013-07. Cooperative particle swarm optimization for multiobjective transportation planning in APPLIED INTELLIGENCE
  • 2014-03. An optimization algorithm inspired by the States of Matter that improves the balance between exploration and exploitation in APPLIED INTELLIGENCE
  • 2012-10. Solving Japanese nonograms by Taguchi-based genetic algorithm in APPLIED INTELLIGENCE
  • 2012-06. A compact genetic algorithm for the network coding based resource minimization problem in APPLIED INTELLIGENCE
  • 2007-11. A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm in JOURNAL OF GLOBAL OPTIMIZATION
  • 2013-07. Control and synchronization of chaotic systems by an improved biogeography-based optimization algorithm in APPLIED INTELLIGENCE
  • 2013-06. An augmented EDA with dynamic diversity control and local neighborhood search for coevolution of optimal negotiation strategies in APPLIED INTELLIGENCE
  • 1997-12. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces in JOURNAL OF GLOBAL OPTIMIZATION
  • 2013-03. A modification to classical evolutionary programming by shifting strategy parameters in APPLIED INTELLIGENCE
  • 2014-03. Cooperative Velocity Updating model based Particle Swarm Optimization in APPLIED INTELLIGENCE
  • 2013-04. The parameter extraction of the thermally annealed Schottky barrier diode using the modified artificial bee colony in APPLIED INTELLIGENCE
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    URI

    http://scigraph.springernature.com/pub.10.1007/s10489-014-0527-z

    DOI

    http://dx.doi.org/10.1007/s10489-014-0527-z

    DIMENSIONS

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