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The Scientific World Journal
Volume 2013 (2013), Article ID 409167, 8 pages
http://dx.doi.org/10.1155/2013/409167
Research Article

A New Logistic Dynamic Particle Swarm Optimization Algorithm Based on Random Topology

1School of Computer Science and Engineering, Southeast University, Nanjing 211189, China
2Provincial Key Laboratory for Computer Information Processing Technology, Soochow University, Suzhou 215006, China

Received 17 April 2013; Accepted 19 May 2013

Academic Editors: P. Agarwal, S. Balochian, and V. Bhatnagar

Copyright © 2013 Qingjian Ni and Jianming Deng. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [12 citations]

The following is the list of published articles that have cited the current article.

  • Jiaheng Qiu, Ray-Bing Chen, Weichung Wang, and Weng Kee Wong, “Using animal instincts to design efficient biomedical studies via particle swarm optimization,” Swarm and Evolutionary Computation, 2014. View at Publisher · View at Google Scholar
  • Zheping Yan, Chao Deng, Dongnan Chi, Tao Chen, and Shuping Hou, “Path Planning Method for UUV Homing and Docking in Movement Disorders Environment,” The Scientific World Journal, vol. 2014, pp. 1–13, 2014. View at Publisher · View at Google Scholar
  • M. J. Mahmoodabadi, M. Taherkhorsandi, and A. Bagheri, “Pareto Design of State Feedback Tracking Control of a Biped Robot via Multiobjective PSO in Comparison with Sigma Method and Genetic Algorithms: Modified NSGAII and MATLAB’s Toolbox,” The Scientific World Journal, vol. 2014, pp. 1–8, 2014. View at Publisher · View at Google Scholar
  • Zheping Yan, Chao Deng, Benyin Li, and Jiajia Zhou, “Novel Particle Swarm Optimization and Its Application in Calibrating the Underwater Transponder Coordinates,” Mathematical Problems in Engineering, 2014. View at Publisher · View at Google Scholar
  • Qingjian Ni, and Jianming Deng, “Analysis of Population Diversity of Dynamic Probabilistic Particle Swarm Optimization Algorithms,” Mathematical Problems in Engineering, 2014. View at Publisher · View at Google Scholar
  • Yudong Zhang, Shuihua Wang, and Genlin Ji, “A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications,” Mathematical Problems in Engineering, vol. 2015, pp. 1–38, 2015. View at Publisher · View at Google Scholar
  • Yang Chen, Yancheng Liu, Chuan Wang, and Rui Ma, “Associations between population topologies and Gaussian dynamic particle swarm performance,” International Journal of Modelling, Identification and Control, vol. 24, no. 2, pp. 138–148, 2015. View at Publisher · View at Google Scholar
  • Qingjian Ni, Xushan Yin, Kangwei Tian, and Yuqing Zhai, “Particle swarm optimization with dynamic random population topology strategies for a generalized portfolio selection problem,” Natural Computing, vol. 16, no. 1, pp. 31–44, 2016. View at Publisher · View at Google Scholar
  • M. Hajihassani, D. Jahed Armaghani, and R. Kalatehjari, “Applications of Particle Swarm Optimization in Geotechnical Engineering: A Comprehensive Review,” Geotechnical and Geological Engineering, 2017. View at Publisher · View at Google Scholar
  • Moslem Fatehi, Hooshang Asadi Haroni, and Amin Hossein Morshedy, “Designing infill directional drilling in mineral exploration by using particle swarm optimization algorithm,” Arabian Journal of Geosciences, vol. 10, no. 22, 2017. View at Publisher · View at Google Scholar
  • Nandar Lynn, Mostafa Z. Ali, and Ponnuthurai Nagaratnam Suganthan, “Population topologies for particle swarm optimization and differential evolution,” Swarm and Evolutionary Computation, 2017. View at Publisher · View at Google Scholar
  • S. Sarathambekai, and K. Umamaheswari, “Task Scheduling in Distributed Systems Using Heap Intelligent Discrete Particle Swarm Optimization,” Computational Intelligence, 2017. View at Publisher · View at Google Scholar