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A Novel Efficient Mutation for Evolutionary Design of Combinational Logic Circuits

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9921))

Abstract

In this paper we investigate evolutionary mechanisms and propose a new mutation operator for the evolutionary design of Combinational Logic Circuits (CLCs). Understanding the root causes of evolutionary success is critical to improving existing techniques. Our focus is two-fold: to analyze beneficial mutations in Cartesian Genetic Programming, and to create an efficient mutation operator for digital CLC design. In the experiments performed the mutation proposed is better than or equivalent to traditional mutation.

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References

  1. Alba, E., Luque, G., Coello Coello, C.A., Hernández Luna, E.: Comparative study of serial and parallel heuristics used to design combinational logic circuits. Optim. Methods Softw. 22(3), 485–509 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  2. Coello, C.A.C., Aguirre, A.H., Buckles, B.P.: Evolutionary multiobjective design of combinational logic circuits. In: Proceedings of 2nd NASA/DoD Workshop on Evolvable Hardware, pp. 161–170. IEEE (2000)

    Google Scholar 

  3. Coello, C.A.C., Alba, E., Luque, G.: Comparing different serial and parallel heuristics to design combinational logic circuits. In: Proceedings of NASA/DoD Conference on Evolvable Hardware, pp. 3–12. IEEE (2003)

    Google Scholar 

  4. Coello, C.A.C., Christiansen, A.D., Aguirre, A.H.: Use of evolutionary techniques to automate the design of combinational circuits. Int. J. Smart Eng. Syst. Des. 2, 299–314 (2000)

    Google Scholar 

  5. Coello, C.A.C., Luna, E.H., Hernández-Aguirre, A.: Use of particle swarm optimization to design combinational logic circuits. In: Tyrrell, A.M., Haddow, P.C., Torresen, J. (eds.) ICES 2003. LNCS, vol. 2606, pp. 398–409. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  6. Coello, C.A.C., Zavala, R.L., García, B.M., Hernández-Aguirre, A.: Ant colony system for the design of combinational logic circuits. In: Miller, J.F., Thompson, A., Thompson, P., Fogarty, T.C. (eds.) ICES 2000. LNCS, vol. 1801, pp. 21–30. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  7. Ercegovac, M.D., Moreno, J.H., Lang, T.: Introduction to Digital Systems. Wiley, Hoboken (1998)

    Google Scholar 

  8. Gajda, Z., Sekanina, L.: An efficient selection strategy for digital circuit evolution. In: Tempesti, G., Tyrrell, A.M., Miller, J.F. (eds.) ICES 2010. LNCS, vol. 6274, pp. 13–24. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  9. García, B.M., Coello, C.A.C.: An approach based on the use of the ant system to design combinational logic circuits. Mathw. Soft Comput. 9(3), 235–250 (2002)

    MathSciNet  MATH  Google Scholar 

  10. Goldman, B.W., Punch, W.F.: Reducing wasted evaluations in cartesian genetic programming. In: Krawiec, K., Moraglio, A., Hu, T., Etaner-Uyar, A.Ş., Hu, B. (eds.) EuroGP 2013. LNCS, vol. 7831, pp. 61–72. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  11. Goldman, B.W., Punch, W.F.: Analysis of cartesian genetic programming’s evolutionary mechanisms. IEEE Trans. Evol. Comput. 19(3), 359–373 (2015)

    Article  Google Scholar 

  12. Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection, vol. 1. MIT Press, Cambridge (1992)

    MATH  Google Scholar 

  13. Luke, S., Panait, L.: A comparison of bloat control methods for genetic programming. Evol. Comput. 14(3), 309–344 (2006)

    Article  Google Scholar 

  14. Manfrini, F., Barbosa, H.J.C., Bernardino, H.S.: Optimization of combinational logic circuits through decomposition of truth table and evolution of sub-circuits. In: IEEE Congress on Evolutionary Computation (CEC), pp. 945–950 (2014)

    Google Scholar 

  15. Miller, J.F.: An empirical study of the efficiency of learning Boolean functions using a cartesian genetic programming approach. In: Proceedings of Genetic and Evolutionary Computation Conference, vol. 2, pp. 1135–1142 (1999)

    Google Scholar 

  16. Miller, J.F.: Cartesian genetic programming. Springer, Berlin (2011)

    Book  MATH  Google Scholar 

  17. Miller, J.F., Smith, S.L.: Redundancy and computational efficiency in cartesian genetic programming. IEEE Trans. Evol. Comput. 10(2), 167–174 (2006)

    Article  Google Scholar 

  18. Tocci, R.J., Widmer, N.S., Moss, G.L.: Digital Systems. Pearson, Upper Saddle River (2011)

    Google Scholar 

  19. Turner, A.J., Miller, J.F.: Recurrent cartesian genetic programming. In: Bartz-Beielstein, T., Branke, J., Filipič, B., Smith, J. (eds.) PPSN 2014. LNCS, vol. 8672, pp. 476–486. Springer, Heidelberg (2014)

    Google Scholar 

  20. Turner, A.J., Miller, J.F.: Neutral genetic drift: an investigation using cartesian genetic programming. Genet. Program. Evol. Mach. 16(4), 531–558 (2015)

    Article  Google Scholar 

  21. Vasicek, Z.: Cartesian GP in optimization of combinational circuits with hundreds of inputs and thousands of gates. In: Machado, P., et al. (eds.) EuroGP 2015. LNCS, vol. 9025, pp. 139–150. Springer, Berlin (2015)

    Google Scholar 

  22. Walker, J.A., Miller, J.F.: The automatic acquisition, evolution and reuse of modules in cartesian genetic programming. IEEE Trans. Evol. Comput. 12(4), 397–417 (2008)

    Article  Google Scholar 

  23. Yu, T., Miller, J.F.: Neutrality and the evolvability of boolean function landscape. In: Miller, J., Tomassini, M., Lanzi, P.L., Ryan, C., Tetamanzi, A.G.B., Langdon, W.B. (eds.) EuroGP 2001. LNCS, vol. 2038, p. 204. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

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Acknowledgment

The authors would like to thank the support provided by CNPq (grant 310778/2013-1), FAPEMIG (grants APQ-03414-15 and PEE-00726-16), and PPGMC/UFJF.

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Correspondence to Helio J. C. Barbosa .

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Manfrini, F.A.L., Bernardino, H.S., Barbosa, H.J.C. (2016). A Novel Efficient Mutation for Evolutionary Design of Combinational Logic Circuits. In: Handl, J., Hart, E., Lewis, P., López-Ibáñez, M., Ochoa, G., Paechter, B. (eds) Parallel Problem Solving from Nature – PPSN XIV. PPSN 2016. Lecture Notes in Computer Science(), vol 9921. Springer, Cham. https://doi.org/10.1007/978-3-319-45823-6_62

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  • DOI: https://doi.org/10.1007/978-3-319-45823-6_62

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45822-9

  • Online ISBN: 978-3-319-45823-6

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