BazEkon - Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie

BazEkon home page

Meny główne

Autor
Al-Rifaie Mohammad Majid (Goldsmiths University of London)
Tytuł
Dispersive Flies Optimisation
Źródło
Annals of Computer Science and Information Systems, 2014, vol. 2, s. 529 - 538, rys., tab., bibliogr. 27 poz.
Słowa kluczowe
Optymalizacja, Algorytmy, Środowisko przyrodnicze
Optimalization, Algorithms, Natural environment
Uwagi
summ.
Abstrakt
One of the main sources of inspiration for techniques applicable to complex search space and optimisation problems is nature. This paper proposes a new metaheuristic - Dispersive Flies Optimisation or DFO - whose inspiration is beckoned from the swarming behaviour of flies over food sources in nature. The simplicity of the algorithm, which is the implementation of one such paradigm for continuous optimisation, facilitates the analysis of its behaviour. A series of experimental trials confirms the promising performance of the optimiser over a set of benchmarks, as well as its competitiveness when compared against few other well-known population based algorithms. In addition to diversity, the performance of the newly introduced algorithm is investigated using the three performance measures of accuracy, efficiency and reliability.(original abstract)
Pełny tekst
Pokaż
Bibliografia
Pokaż
  1. al-Rifaie M. M. and Aber A., "Identifying metastasis in bone scans with stochastic diffusion search," in Information Technology in Medicine and Education (ITME). IEEE, 2012. [Online]. Available: http://dx.doi.org/10.1109/ITiME.2012.6291355
  2. Back T., Fogel D. B., and Michalewicz Z., Handbook of evolutionary computation. IOP Publishing Ltd., 1997.
  3. Belkin J. N., Ehmann N., and Heid G., "Preliminary field observations on the behavior of the adults of anopheles franciscanus mccracken in southern california," Mosq News, vol. 11, pp. 23-31, 1951.
  4. Blickle R. L., "Observations on the hovering and mating of tabanus bishopp," Stone. Ann. Entomol. Soc. 52, pp. 183-90, 1958.
  5. Bratton D. and Kennedy J., "Defining a standard for particle swarm optimization," in Proc of the Swarm Intelligence Symposium. Honolulu, Hawaii, USA: IEEE, 2007, pp. 120-127.
  6. Dorigo M., Birattari M., and Stutzle T., "Ant colony optimization," Computational Intelligence Magazine, IEEE, vol. 1, no. 4, pp. 28-39, 2006.
  7. Downes J., "Assembly and mating in the biting nematocera," Intern. Congr. Entomol. Proc. 10th, Montreal, pp. 425-34, 1958.
  8. Downes J., "Observations on the swarming flight and mating of culicoides (diptera: Ceratopogonidae) 1," Transactions of the Royal Entomological Society of London, vol. 106, no. 5, pp. 213-236, 1955.
  9. Downes J., "The swarming and mating flight of diptera," Annual review of entomology, vol. 14, no. 1, pp. 271-298, 1969.
  10. Gehlhaar D. and Fogel D., "Tuning evolutionary programming for conformationally flexible molecular docking," in Evolutionary Programming V: Proc. of the Fifth Annual Conference on Evolutionary Programming, 1996, pp. 419-429.
  11. Goldberg D. E., Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA, 1989.
  12. Heppner F. and Grenander U., "A stochastic nonlinear model for coordinated bird flocks." American Association for the Advancement of Science, Washington, DC(USA)., 1990.
  13. Kennedy J. and Eberhart R. C., "Particle swarm optimization," in Proceedings of the IEEE International Conference on Neural Networks, vol. IV. Piscataway, NJ: IEEE Service Center, 1995, pp. 1942-1948.
  14. Klassen W. and Hocking B., "The influence of a deep river valley system on the dispersal of aedes mosquitos," Bulletin of Entomological Research, vol. 55, no. 02, pp. 289-304, 1964.
  15. Knab F., "The swarming of culex pipiens," Psyche: A Journal of Entomology, vol. 13, no. 5, pp. 123-133, 1906.
  16. Lee C. -Y. and Yao X., "Evolutionary programming using mutations based on the lévy probability distribution," Evolutionary Computation, IEEE Transactions on, vol. 8, no. 1, pp. 1-13, 2004.
  17. Nielsen H. T., "Swarming and some other habits of mansonia perturbans and psorophora ferox (diptera: Culicidae)," Behaviour, pp. 67-89, 1964.
  18. Olorunda O. and Engelbrecht A. P., "Measuring exploration/exploitation in particle swarms using swarm diversity," in Evolutionary Computation, 2008. CEC 2008.(IEEE World Congress on Computational Intelligence). IEEE Congress on. IEEE, 2008, pp. 1128-1134.
  19. Peña J., "Theoretical and empirical study of particle swarms with additive stochasticity and different recombination operators," in Proceedings of the 10th annual conference on Genetic and evolutionary computation, ser. GECCO '08. New York, NY, USA: ACM, 2008, pp. 95-102. [Online]. Available: http://doi.acm.org/10.1145/1389095.1389109
  20. Roth L. M., "A study of mosquito behavior. an experimental laboratory study of the sexual behavior of aedes aegypti (linnaeus)," American Midland Naturalist, vol. 40, no. 2, pp. 265-352, 1948.
  21. Storn R. and Price K., "Differential evolution - a simple and efficient adaptive scheme for global optimization over continuous spaces," 1995, tR-95-012, [online]. Available: http://www.icsi.berkeley.edu/ storn/litera.html.
  22. Suganthan P. N., Hansen N., Liang J. J., Deb K., Chen Y. P., Auger A., and Tiwari S., "Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization," Nanyang Technological University, Singapore and Kanpur Genetic Algorithms Laboratory, IIT Kanpur, Tech. Rep., 2005.
  23. Sullivan R. T., "Insect swarming and mating," The Florida Entomologist, vol. 64, no. 1, pp. 44-65, 1981.
  24. Thomsen R., "Flexible ligand docking using evolutionary algorithms: investigating the effects of variation operators and local search hybrids," Biosystems, vol. 72, no. 1-2, pp. 57-73, 2003.
  25. Vesterstrom J. and Thomsen R., "A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems," in Evolutionary Computation, 2004. CEC2004. Congress on, vol. 2, 2004, pp. 1980-1987.
  26. Wiegmann B. M. and Yeates D. K., Tree of Life: Diptera. The Tree of Life Web Project, 1996.
  27. Yao X., Liu Y., and Lin G., "Evolutionary programming made faster," Evolutionary Computation, IEEE Transactions on, vol. 3, no. 2, pp. 82-102, 1999.
Cytowane przez
Pokaż
ISSN
2300-5963
Język
eng
Udostępnij na Facebooku Udostępnij na Twitterze Udostępnij na Google+ Udostępnij na Pinterest Udostępnij na LinkedIn Wyślij znajomemu