Sistema de control para computación evolutiva basado en redes complejas
Corresponding Author(s) : Víctor Bucheli Guerrero
Investigación e Innovación en Ingenierías,
Vol. 8 Núm. 2 (2020): Julio - Diciembre
Resumen
Objetivo: Implementar un mecanismo de control para las dinámicas de población de un algoritmo evolutivo basado en redes complejas. Se plantea la hipótesis de que la estrategia guiada por una red compleja tiene mejores resultados que un algoritmo evolutivo tradicional. Metodología: Se estudia la convergencia del modelo propuesto frente a la solución evolutiva tradicional. Se realizaron análisis estadísticos frente a los resultados experimentales obtenidos para diferentes problemas de optimización. Resultados: Las estrategias en las que se integran redes de pequeño mundo como mecanismo de control de las dinámicas de población, tienen un mejor desempeño en general que otras topologías de red. Conclusiones: La integración de una estructura de red compleja, como una red subyacente en la dinámica de un algoritmo evolutivo, muestra una ventaja competitiva en relación con estrategias tradicionales, específicamente las redes de pequeño mundo muestran un mejor desempeño.
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- L. Fogel, A. Owens, and M. Walsh, Artificial intelligence through simulated evolution. Chichester, WS, UK: Wiley, 1966.
- D.B. Fogel, “Evolutionary Computation: Toward a New Philosophy of Machine Intelligence”, IEEE Press, 1995.
- M. Raschip, M. Breaban, and C. Croitoru, “Evolutionary Computation in Constraint Satisfaction”, vol. 02, 2010.
- R. Caponetto, “Chaotic sequences to improve the performance of evolutionary algorithms”, IEEE Transactions on Evolutionary Computation, vol. 7, pp. 289–304, 2003.
- M.V.D.K. Tasoulis, V.P. Plagianakos, “Clustering in evolutionary algorithms to efficiently compute simultaneously local and global minima”, Proceedings of the IEEE Congress on Evolutionary Computation, 2005.
- A. E. Eiben, R. Hinterding, and Z. Michalewicz, “Parameter control in evolutionary algorithms,” IEEE Transactions on Evolutionary Computation, vol. 3, no. 2, pp. 124–141, July 1999.
- I. Zelinka, D. Davendra, V. Snasel, R. Jasek, R. Senkerık, and Z. Oplatkova, “Preliminary investigation on relations between complex networks and evolutionary algorithms dynamics”, 2010 International Conference on Computer Information Systems and Industrial Management Applications, CISIM, pp. 148–153, 2010.
- S. N. Dorogovtsev and J. F. F. Mendes, Evolution of Networks: From Biological Nets to the Internet and WWW (Physics), New York, NY, USA: Oxford University Press, Inc., 2003.
- I. Zelinka, D. Davendra, S. Roman, and J. Roman, “Do Evolutionary Algorithm Dynamics Create Complex Network Structures?”, Complex Systems, vol. 20, n°. 2, pp. 127–140, 2011.
- I. Zelinka, “Investigation on relationship between complex networks and evolutionary algorithms dynamics", AIP Conference Proceedings, vol. 1389, pp.1011–1014, 2011.
- I. Zelinka, “IWCFTA 2012 Keynote Speech III on Close Relations of Evolutionary Dynamics, Chaos and Complexity”, IEEE Xplore, 2012..
- I. Zelinka, D. D. Davendra, M. Chadli, and R. Senkerik, “Evolutionary Dynamics as The Structure of Complex Networks”, Springer, Berlin, Heidelberg, pp. 215–243, 2013.
- I. Zelinka, D. Davendra, J. Lampinen, R. Senkerik, and M. Pluhacek, “Evolutionary algorithms dynamics and its hidden complex network structures”, IEEE Congress on Evolutionary Computation, CEC , 2014.
- P. K. Storn, “Differential evolution—a simple and efficient adaptive scheme for global optimization over continuous spaces”, Technical Report TR-95-012, ICSI, 1995.
- V. M. Plagianakos., and K. Tasoulis, “A review of major application areas of differential evolution”, Advances in differential evolution, vol143 of studies in computational intelligence. Springer, Berlin, 2008.
- S. P. Qin AK, “Self-adaptive differential evolution algorithm for numerical optimization.”, Proceedings of the IEEE congress on evolutionary computation, 2005.
- J. Lampinen., and I. Zelinka, Mechanical engineering design optimization by differential evolution, New ideas in optimization. New York: McGraw-Hill, 1999.
- S. N. Dorogovtsev and J. F. F. Mendes, “Evolution of networks”, Advances in Physics, vol. 51, n°. 4, pp. 1079–1187, 2002.
- L. A. N. Amaral, A. Scala, M. Barthelemy, and H. E. Stanley, “Classes of small-world networks”, Proceedings of the National Academy of Sciences, vol. 97, n°. 21, pp. 11 149–152, September 2000.
- I. Zelinka, “SOMA — Self-Organizing Migrating Algorithm.”, Berlin, Heidelberg: Springer Berlin Heidelberg, 2004.
- P. K. Storn R, “Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces”, J Glob Optim, 1997.
- I. Zelinka, L. Tomaszek, and V. Snasel, “On Evaluation of Evolutionary Networks Using New Temporal Centralities Algorithm,”2015 International Conference on Intelligent Networking and Collaborative Systems, IEEE
- INCoS 2015, 2015.
- L. Sheng, F. Chen, and H. Wang, “A Review on complex network dynamics in evolutionary algorithm,” IEEE Xplore, 2016.
- Yang Yinghui, Li Jianhua, Shen Di, Nan Mingli, Cui Qiong, “Evolutionary dynamics analysis of complex network with fusion nodes and overlap edges”, Journal of Systems Engineering and Electronics, 2018
- C. Pizzuti,“Evolutionary Computation for Community Detection in Networks: A Review” ,IEEE Transactions on Evolutionary Computation, 2017
- Yang Liu, Xi Wang, Jürgen Kurths, “Framework of Evolutionary Algorithm for Investigation of Influential Nodes in Complex Networks”, IEEE Transactions on Evolutionary Computation, 2019
- D. J. W. S. H. Strogatz, “Collective dynamics of small-world networks”, Nature, 1998.
- T. Back, “Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms”, J Glob Optim, 1995.
- C. Vanaret, J.-B. Gotteland, N. Durand, and J.M. Alliot, “Certified global minima for a benchmark of difficult optimization problems,” Mathematics, Computer Science, 2014.
- S. Picek, M. Golub., and D. Jakobovic “On the Analysis of Experimental Results in Evolutionary Computation”, Proceedings of the 35th International Convention MIPRO, 2012
- J. Triana, V. Bucheli, Redes complejas en computación evolutiva (repositorio)., 2020. Disponible en: https://github.com/jodatm/RedesComplejasComputacionEvolutiva
Referencias
L. Fogel, A. Owens, and M. Walsh, Artificial intelligence through simulated evolution. Chichester, WS, UK: Wiley, 1966.
D.B. Fogel, “Evolutionary Computation: Toward a New Philosophy of Machine Intelligence”, IEEE Press, 1995.
M. Raschip, M. Breaban, and C. Croitoru, “Evolutionary Computation in Constraint Satisfaction”, vol. 02, 2010.
R. Caponetto, “Chaotic sequences to improve the performance of evolutionary algorithms”, IEEE Transactions on Evolutionary Computation, vol. 7, pp. 289–304, 2003.
M.V.D.K. Tasoulis, V.P. Plagianakos, “Clustering in evolutionary algorithms to efficiently compute simultaneously local and global minima”, Proceedings of the IEEE Congress on Evolutionary Computation, 2005.
A. E. Eiben, R. Hinterding, and Z. Michalewicz, “Parameter control in evolutionary algorithms,” IEEE Transactions on Evolutionary Computation, vol. 3, no. 2, pp. 124–141, July 1999.
I. Zelinka, D. Davendra, V. Snasel, R. Jasek, R. Senkerık, and Z. Oplatkova, “Preliminary investigation on relations between complex networks and evolutionary algorithms dynamics”, 2010 International Conference on Computer Information Systems and Industrial Management Applications, CISIM, pp. 148–153, 2010.
S. N. Dorogovtsev and J. F. F. Mendes, Evolution of Networks: From Biological Nets to the Internet and WWW (Physics), New York, NY, USA: Oxford University Press, Inc., 2003.
I. Zelinka, D. Davendra, S. Roman, and J. Roman, “Do Evolutionary Algorithm Dynamics Create Complex Network Structures?”, Complex Systems, vol. 20, n°. 2, pp. 127–140, 2011.
I. Zelinka, “Investigation on relationship between complex networks and evolutionary algorithms dynamics", AIP Conference Proceedings, vol. 1389, pp.1011–1014, 2011.
I. Zelinka, “IWCFTA 2012 Keynote Speech III on Close Relations of Evolutionary Dynamics, Chaos and Complexity”, IEEE Xplore, 2012..
I. Zelinka, D. D. Davendra, M. Chadli, and R. Senkerik, “Evolutionary Dynamics as The Structure of Complex Networks”, Springer, Berlin, Heidelberg, pp. 215–243, 2013.
I. Zelinka, D. Davendra, J. Lampinen, R. Senkerik, and M. Pluhacek, “Evolutionary algorithms dynamics and its hidden complex network structures”, IEEE Congress on Evolutionary Computation, CEC , 2014.
P. K. Storn, “Differential evolution—a simple and efficient adaptive scheme for global optimization over continuous spaces”, Technical Report TR-95-012, ICSI, 1995.
V. M. Plagianakos., and K. Tasoulis, “A review of major application areas of differential evolution”, Advances in differential evolution, vol143 of studies in computational intelligence. Springer, Berlin, 2008.
S. P. Qin AK, “Self-adaptive differential evolution algorithm for numerical optimization.”, Proceedings of the IEEE congress on evolutionary computation, 2005.
J. Lampinen., and I. Zelinka, Mechanical engineering design optimization by differential evolution, New ideas in optimization. New York: McGraw-Hill, 1999.
S. N. Dorogovtsev and J. F. F. Mendes, “Evolution of networks”, Advances in Physics, vol. 51, n°. 4, pp. 1079–1187, 2002.
L. A. N. Amaral, A. Scala, M. Barthelemy, and H. E. Stanley, “Classes of small-world networks”, Proceedings of the National Academy of Sciences, vol. 97, n°. 21, pp. 11 149–152, September 2000.
I. Zelinka, “SOMA — Self-Organizing Migrating Algorithm.”, Berlin, Heidelberg: Springer Berlin Heidelberg, 2004.
P. K. Storn R, “Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces”, J Glob Optim, 1997.
I. Zelinka, L. Tomaszek, and V. Snasel, “On Evaluation of Evolutionary Networks Using New Temporal Centralities Algorithm,”2015 International Conference on Intelligent Networking and Collaborative Systems, IEEE
INCoS 2015, 2015.
L. Sheng, F. Chen, and H. Wang, “A Review on complex network dynamics in evolutionary algorithm,” IEEE Xplore, 2016.
Yang Yinghui, Li Jianhua, Shen Di, Nan Mingli, Cui Qiong, “Evolutionary dynamics analysis of complex network with fusion nodes and overlap edges”, Journal of Systems Engineering and Electronics, 2018
C. Pizzuti,“Evolutionary Computation for Community Detection in Networks: A Review” ,IEEE Transactions on Evolutionary Computation, 2017
Yang Liu, Xi Wang, Jürgen Kurths, “Framework of Evolutionary Algorithm for Investigation of Influential Nodes in Complex Networks”, IEEE Transactions on Evolutionary Computation, 2019
D. J. W. S. H. Strogatz, “Collective dynamics of small-world networks”, Nature, 1998.
T. Back, “Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms”, J Glob Optim, 1995.
C. Vanaret, J.-B. Gotteland, N. Durand, and J.M. Alliot, “Certified global minima for a benchmark of difficult optimization problems,” Mathematics, Computer Science, 2014.
S. Picek, M. Golub., and D. Jakobovic “On the Analysis of Experimental Results in Evolutionary Computation”, Proceedings of the 35th International Convention MIPRO, 2012
J. Triana, V. Bucheli, Redes complejas en computación evolutiva (repositorio)., 2020. Disponible en: https://github.com/jodatm/RedesComplejasComputacionEvolutiva