A Complementary Cyber Swarm Algorithm

  • Authors:

  • Peng-Yeng Yin;Fred Glover;Manuel Laguna;Jia-Xian Zhu

  • Affiliations:

  • National Chi Nan University, Taiwan;OptTek Systems, Inc., USA;University of Colorado, USA;National Chi Nan University, Taiwan

  • Venue:
  • International Journal of Swarm Intelligence Research
  • Year:
  • 2011

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Abstract

A recent study Yin et al., 2010 showed that combining particle swarm optimization PSO with the strategies of scatter search SS and path relinking PR produces a Cyber Swarm Algorithm that creates a more effective form of PSO than methods that do not incorporate such mechanisms. This paper proposes a Complementary Cyber Swarm Algorithm C/CyberSA that performs in the same league as the original Cyber Swarm Algorithm but adopts different sets of ideas from the tabu search TS and the SS/PR template. The C/CyberSA exploits the guidance information and restriction information produced in the history of swarm search and the manipulation of adaptive memory. Responsive strategies using long term memory and path relinking implementations are proposed that make use of critical events encountered in the search. Experimental results with a large set of challenging test functions show that the C/CyberSA outperforms two recently proposed swarm-based methods by finding more optimal solutions while simultaneously using a smaller number of function evaluations. The C/CyberSA approach further produces improvements comparable to those obtained by the original CyberSA in relation to the Standard PSO 2007 method Clerc, 2008.