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The Scientific World Journal
Volume 2013, Article ID 860289, 12 pages
http://dx.doi.org/10.1155/2013/860289
Research Article

On the Performance of Linear Decreasing Inertia Weight Particle Swarm Optimization for Global Optimization

School of Mathematics, Statistics, and Computer Science, University of Kwazulu-Natal, Private Bag X54001, Durban 4000, South Africa

Received 9 July 2013; Accepted 4 September 2013

Academic Editors: P. Melin, G. Terracina, and G. Wei

Copyright © 2013 Martins Akugbe Arasomwan and Aderemi Oluyinka Adewumi. 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 [23 citations]

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

  • K. G. Li, Mohd Ibrahim Shapiai, Asrul Adam, and Zuwairie Ibrahim, “Feature scaling for EEG human concentration using particle swarm optimization,” 2016 8th International Conference on Information Technology and Electrical Engineering (ICITEE), pp. 1–6, . View at Publisher · View at Google Scholar
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  • Aderemi Oluyinka Adewumi, and Akugbe Martins Arasomwan, “An improved particle swarm optimiser based on swarm success rate for global optimisation problems,” Journal of Experimental & Theoretical Artificial Intelligence, pp. 1–43, 2014. View at Publisher · View at Google Scholar
  • Akugbe Martins Arasomwan, and Aderemi Oluyinka Adewumi, “An Investigation into the Performance of Particle Swarm Optimization with Various Chaotic Maps,” Mathematical Problems in Engineering, 2014. View at Publisher · View at Google Scholar
  • Martins Akugbe Arasomwan, and Aderemi Oluyinka Adewumi, “Improved Particle Swarm Optimization with a Collective Local Unimodal Search for Continuous Optimization Problems,” Scientific World Journal, 2014. View at Publisher · View at Google Scholar
  • Aderemi Oluyinka Adewumi, and Akugbe Martins Arasomwan, “Improved Particle Swarm Optimizer with Dynamically Adjusted Search Space and Velocity Limits for Global Optimization,” International Journal on Artificial Intelligence Tools, vol. 24, no. 05, pp. 1550017, 2015. View at Publisher · View at Google Scholar
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  • Aderemi Oluyinka Adewumi, and Akugbe Martins Arasomwan, “Improved particle swarm optimization based on greedy and adaptive features,” IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - SIS 2014: 2014 IEEE Symposium on Swarm Intelligence, Proceedings, pp. 237–242, 2015. View at Publisher · View at Google Scholar
  • Micheal O. Olusanya, Martins A. Arasomwan, and Aderemi O. Adewumi, “Particle Swarm Optimization Algorithm for Optimizing Assignment of Blood in Blood Banking System,” Computational and Mathematical Methods in Medicine, vol. 2015, pp. 1–12, 2015. View at Publisher · View at Google Scholar
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  • Akugbe Martins Arasomwan, and Aderemi Oluyinka Adewumi, “On the Hybridization of Particle Swarm Optimization Technique for Continuous Optimization Problems,” Advances in Swarm Intelligence, vol. 9712, pp. 358–366, 2016. View at Publisher · View at Google Scholar
  • Jianhua Liu, Xiaodong Li, and Yi Mei, “An analysis of the inertia weight parameter for binary particle swarm optimization,” IEEE Transactions on Evolutionary Computation, vol. 20, no. 5, pp. 666–681, 2016. View at Publisher · View at Google Scholar
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  • Valarmathi, and Sheela, “A comprehensive survey on Task Scheduling for parallel workloads based on Particle Swarm optimisation under Cloud environment,” Proceedings of the 2017 2nd International Conference on Computing and Communications Technologies, ICCCT 2017, pp. 81–86, 2017. View at Publisher · View at Google Scholar
  • Hongguang Li, Wenrui Ding, Xianbin Cao, and Chunlei Liu, “Image Registration and Fusion of Visible and Infrared Integrated Camera for Medium-Altitude Unmanned Aerial Vehicle Remote Sensing,” Remote Sensing, vol. 9, no. 5, pp. 441, 2017. View at Publisher · View at Google Scholar
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  • Suchao Xie, Haihong Li, Chengxing Yang, and Shuguang Yao, “Crashworthiness optimisation of a composite energy-absorbing structure for subway vehicles based on hybrid particle swarm optimisation,” Structural and Multidisciplinary Optimization, 2018. View at Publisher · View at Google Scholar
  • Delin Wang, Ningning Ma, Mengxi Wei, and Yingchao Liu, “Parameters tuning of power system stabilizer PSS4B using hybrid particle swarm optimization algorithm,” International Transactions on Electrical Energy Systems, pp. e2598, 2018. View at Publisher · View at Google Scholar
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  • Zhao Yang, Ming-Qing Xiao, Lei Zhang, Xi-Lang Tang, Ya-Wei Ge, De-Long Feng, and Hai-Fang Song, “A double-loop hybrid algorithm for the traveling salesman problem with arbitrary neighbourhoods,” European Journal of Operational Research, vol. 265, no. 1, pp. 65–80, 2018. View at Publisher · View at Google Scholar