Special Issue: Bio-Inspired Optimization Techniques for High Performance Computing

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References

  1. 1.

    Dorigo, M., Bonabeau, E. and Theraulaz, G., “Ant algorithms and stigmergy,” Future Generation Computer Systems, 16, 9, pp. 851–871, 2000.

    Article  Google Scholar 

  2. 2.

    Folino, G., Mastroianni, C., Fragopoulou, P. and Suzuki, J. eds., 2nd Workshop on Bio-Inspired and Self-* Algorithms for Distributed Systems, ACM, June 2010.

  3. 3.

    Folino, G. and Spezzano, G., “An autonomic tool for building self organizing grid-enabled applications,” Future Generation Comp. Syst., 23, 5, pp. 671–679, 2007.

    Article  Google Scholar 

  4. 4.

    Forestiero, A., Mastroianni, C. and Spezzano, G., “So-grid: A self organizing grid featuring bio-inspired algorithms,” TAAS, 3, 2, 2008.

  5. 5.

    Kennedy, J. and Eberhart, R., “Particle swarm optimization,” in Neural Networks, 1995. Proc., IEEE International Conference on, 4, pp. 1942–1948, August 2002.

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Correspondence to Gianluigi Folino.

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Folino, G., Mastroianni, C. Special Issue: Bio-Inspired Optimization Techniques for High Performance Computing. New Gener. Comput. 29, 125–128 (2011). https://doi.org/10.1007/s00354-011-0101-8

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Keywords

  • Bio-inspired Algorithms
  • Optimization
  • Swarm Intelligence
  • Ant Colony Optimization
  • Parallel and Distributed Algorithms