Skip to main content
Top

2016 | OriginalPaper | Chapter

19. Memetic Algorithms

Authors : Ke-Lin Du, M. N. S. Swamy

Published in: Search and Optimization by Metaheuristics

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

The term meme was coined by Dawkins in 1976 in his book The Selfish Gene [7]. The sociological definition of a meme is the basic unit of cultural transmission or imitation. A meme is the social analog of genes for individuals. Universal Darwinism draws the analogy on the role of genes in genetic evolution to that of memes in a cultural evolutionary process [7]. The science of memetics [3] represents the mind-universe analog to genetics in cultural evolution, ranging the fields of anthropology, biology, cognition, psychology, sociology, and sociobiology. This chapter is dedicated to memetic and cultural algorithms.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Alami J, Imrani AE, Bouroumi A. A multi-population cultural algorithm using fuzzy clustering. Appl Soft Comput. 2007;7(2):506–19.CrossRef Alami J, Imrani AE, Bouroumi A. A multi-population cultural algorithm using fuzzy clustering. Appl Soft Comput. 2007;7(2):506–19.CrossRef
2.
go back to reference Becerra RL, Coello CAC. Cultured differential evolution for constrained optimization. Comput Meth Appl Mech Eng. 2006;195:4303–22.MathSciNetCrossRefMATH Becerra RL, Coello CAC. Cultured differential evolution for constrained optimization. Comput Meth Appl Mech Eng. 2006;195:4303–22.MathSciNetCrossRefMATH
3.
go back to reference Blackmore S. The meme machine. New York: Oxford University Press; 1999. Blackmore S. The meme machine. New York: Oxford University Press; 1999.
4.
go back to reference Botzheim J, Cabrita C, Koczy LT, Ruano AE. Fuzzy rule extraction by bacterial memetic algorithms. Int J Intell Syst. 2009;24(3):1563–8.CrossRefMATH Botzheim J, Cabrita C, Koczy LT, Ruano AE. Fuzzy rule extraction by bacterial memetic algorithms. Int J Intell Syst. 2009;24(3):1563–8.CrossRefMATH
5.
go back to reference Chelouah R, Siarry P. Genetic and Nelder-Mead algorithms hybridized for a more accurate global optimization of continuous multiminima functions. Eur J Oper Res. 2003;148:335–48.MathSciNetCrossRefMATH Chelouah R, Siarry P. Genetic and Nelder-Mead algorithms hybridized for a more accurate global optimization of continuous multiminima functions. Eur J Oper Res. 2003;148:335–48.MathSciNetCrossRefMATH
6.
go back to reference Chung CJ, Reynolds RG. Function optimization using evolutionary programming with self-adaptive cultural algorithms. In: Proceedings of Asia-Pacific conference on simulated evolution and learning, Taejon, Korea, 1996. p. 17–26. Chung CJ, Reynolds RG. Function optimization using evolutionary programming with self-adaptive cultural algorithms. In: Proceedings of Asia-Pacific conference on simulated evolution and learning, Taejon, Korea, 1996. p. 17–26.
7.
go back to reference Dawkins R. The selfish gene. Oxford, UK: Oxford Unive Press; 1976. Dawkins R. The selfish gene. Oxford, UK: Oxford Unive Press; 1976.
8.
go back to reference Digalakis JG, Margaritis KG. A multi-population cultural algorithm for the electrical generator scheduling problem. Math Comput Simul. 2002;60(3):293–301.MathSciNetCrossRefMATH Digalakis JG, Margaritis KG. A multi-population cultural algorithm for the electrical generator scheduling problem. Math Comput Simul. 2002;60(3):293–301.MathSciNetCrossRefMATH
9.
go back to reference Du K-L, Mow WH, Wu WH. New evolutionary search for long low autocorrelation binary sequences. IEEE Trans Aerosp Electron Syst. 2015;51(1):290–303.CrossRef Du K-L, Mow WH, Wu WH. New evolutionary search for long low autocorrelation binary sequences. IEEE Trans Aerosp Electron Syst. 2015;51(1):290–303.CrossRef
10.
go back to reference Farahmand AM, Ahmadabadi MN, Lucas C, Araabi BN. Interaction of culture-based learning and cooperative coevolution and its application to automatic behavior-based system design. IEEE Trans Evol Comput. 2010;14(1):23–57.CrossRef Farahmand AM, Ahmadabadi MN, Lucas C, Araabi BN. Interaction of culture-based learning and cooperative coevolution and its application to automatic behavior-based system design. IEEE Trans Evol Comput. 2010;14(1):23–57.CrossRef
11.
go back to reference Folino G, Pizzuti C, Spezzano G. Combining cellular genetic algorithms and local search for solving satisfiability problems. In: Proceedings of the 12th IEEE international conference on tools with artificial intelligence, Taipei, Taiwan, November 1998. p. 192–198. Folino G, Pizzuti C, Spezzano G. Combining cellular genetic algorithms and local search for solving satisfiability problems. In: Proceedings of the 12th IEEE international conference on tools with artificial intelligence, Taipei, Taiwan, November 1998. p. 192–198.
12.
go back to reference Huy NQ, Soon OY, Hiot LM, Krasnogor N. Adaptive cellular memetic algorithms. Evol Comput. 2009;17(2):231–56.CrossRef Huy NQ, Soon OY, Hiot LM, Krasnogor N. Adaptive cellular memetic algorithms. Evol Comput. 2009;17(2):231–56.CrossRef
13.
go back to reference Karimi A, Siarry P. Global simplex optimization—a simple and efficient metaheuristic for continuous optimization. Eng Appl Artif Intell. 2012;25:48–55.CrossRef Karimi A, Siarry P. Global simplex optimization—a simple and efficient metaheuristic for continuous optimization. Eng Appl Artif Intell. 2012;25:48–55.CrossRef
14.
go back to reference Kendall G, Soubeiga E, Cowling P. Choice function and random hyperheuristics. In: Proceedings of the 4th Asia-Pacific conference on simulated evolution and learning, Singapore, November 2002. p. 667–671. Kendall G, Soubeiga E, Cowling P. Choice function and random hyperheuristics. In: Proceedings of the 4th Asia-Pacific conference on simulated evolution and learning, Singapore, November 2002. p. 667–671.
15.
go back to reference Kirby S. Spontaneous evolution of linguistic structure: an iterated learning model of the emergence of regularity and irregularity. IEEE Trans Evol Comput. 2001;5(2):102–10.MathSciNetCrossRef Kirby S. Spontaneous evolution of linguistic structure: an iterated learning model of the emergence of regularity and irregularity. IEEE Trans Evol Comput. 2001;5(2):102–10.MathSciNetCrossRef
16.
go back to reference Krasnogor N. Studies on the theory and design space of memetic algorithms. PhD Thesis, Faculty Comput Math Eng Bristol, UK, University West of England, 2002. Krasnogor N. Studies on the theory and design space of memetic algorithms. PhD Thesis, Faculty Comput Math Eng Bristol, UK, University West of England, 2002.
17.
go back to reference Lee JT, Lau E, Ho Y-C. The Witsenhausen counterexample: a hierarchical search approach for nonconvex optimization problems. IEEE Trans Autom Control. 2001;46(3):382–97.MathSciNetCrossRefMATH Lee JT, Lau E, Ho Y-C. The Witsenhausen counterexample: a hierarchical search approach for nonconvex optimization problems. IEEE Trans Autom Control. 2001;46(3):382–97.MathSciNetCrossRefMATH
18.
go back to reference Lozano M, Herrera F, Krasnogor N, Molina D. Real-coded memetic algorithms with crossover hill-climbing. Evol Comput. 2004;12(3):273–302.CrossRef Lozano M, Herrera F, Krasnogor N, Molina D. Real-coded memetic algorithms with crossover hill-climbing. Evol Comput. 2004;12(3):273–302.CrossRef
19.
20.
go back to reference Malaek SM, Karimi A. Development of a new global continuous optimization algorithm based on Nelder–Mead Simplex and evolutionary process concepts. In: Proceedings of the 6th international conference on nonlinear problems in aerospace and aviation (ICNPAA), Budapest, Hungary, June 2006. p. 435–447. Malaek SM, Karimi A. Development of a new global continuous optimization algorithm based on Nelder–Mead Simplex and evolutionary process concepts. In: Proceedings of the 6th international conference on nonlinear problems in aerospace and aviation (ICNPAA), Budapest, Hungary, June 2006. p. 435–447.
21.
go back to reference Molina D, Lozano M, Garcia-Martinez C, Herrera F. Memetic algorithms for continuous optimization based on local search chains. Evol Comput. 2010;18(1):27–63.CrossRef Molina D, Lozano M, Garcia-Martinez C, Herrera F. Memetic algorithms for continuous optimization based on local search chains. Evol Comput. 2010;18(1):27–63.CrossRef
22.
go back to reference Molina D, Lozano M, Herrera F. MA-SW-Chains: memetic algorithm based on local search chains for large scale continuous global optimization. In: Proceedings of the IEEE Congress on evolutionary computation (CEC), Barcelona, Spain, July 2010. p. 1–8. Molina D, Lozano M, Herrera F. MA-SW-Chains: memetic algorithm based on local search chains for large scale continuous global optimization. In: Proceedings of the IEEE Congress on evolutionary computation (CEC), Barcelona, Spain, July 2010. p. 1–8.
23.
go back to reference Moscato P. On evolution, search, optimization, genetic algorithms and martial arts: towards memetic algorithms. Technical Report 826, Caltech Concurrent Computation Program, California Institute of Technology, Pasadena, CA, 1989. Moscato P. On evolution, search, optimization, genetic algorithms and martial arts: towards memetic algorithms. Technical Report 826, Caltech Concurrent Computation Program, California Institute of Technology, Pasadena, CA, 1989.
24.
go back to reference Moscato P. Memetic algorithms: a short introduction. In: Corne D, Glover F, Dorigo M, editors. New ideas in optimization. McGraw-Hill; 1999. p. 219–234. Moscato P. Memetic algorithms: a short introduction. In: Corne D, Glover F, Dorigo M, editors. New ideas in optimization. McGraw-Hill; 1999. p. 219–234.
25.
go back to reference Nguyen QH, Ong Y-S, Lim MH. A probabilistic memetic framework. IEEE Trans Evol Comput. 2009;13(3):604–23.CrossRef Nguyen QH, Ong Y-S, Lim MH. A probabilistic memetic framework. IEEE Trans Evol Comput. 2009;13(3):604–23.CrossRef
26.
go back to reference Noman N, Iba H. Enhancing differential evolution performance with local search for high dimensional function optimization. In: Proceedings of genetic and evolutionary computation conference (GECCO), Washington DC, June 2005. p. 967–974. Noman N, Iba H. Enhancing differential evolution performance with local search for high dimensional function optimization. In: Proceedings of genetic and evolutionary computation conference (GECCO), Washington DC, June 2005. p. 967–974.
27.
go back to reference Ong YS, Keane AJ. Meta-Lamarckian learning in memetic algorithms. IEEE Trans Evol Comput. 2004;8(2):99–110.CrossRef Ong YS, Keane AJ. Meta-Lamarckian learning in memetic algorithms. IEEE Trans Evol Comput. 2004;8(2):99–110.CrossRef
28.
go back to reference Peng B, Reynolds RG. Cultural algorithms: knowledge learning in dynamic environments. In: Proceedings of IEEE congress on evolutionary computation, Portland, OR, 2004. p. 1751–1758. Peng B, Reynolds RG. Cultural algorithms: knowledge learning in dynamic environments. In: Proceedings of IEEE congress on evolutionary computation, Portland, OR, 2004. p. 1751–1758.
29.
go back to reference Renders J-M, Bersini H. Hybridizing genetic algorithms with hill-climbing methods for global optimization: two possible ways. In: Proceedings of the 1st IEEE conference on evolutionary computation, Orlando, FL, June 1994, vol. 1. p. 312–317. Renders J-M, Bersini H. Hybridizing genetic algorithms with hill-climbing methods for global optimization: two possible ways. In: Proceedings of the 1st IEEE conference on evolutionary computation, Orlando, FL, June 1994, vol. 1. p. 312–317.
30.
go back to reference Reynolds RG. An introduction to cultural algorithms. In: Sebald AV, Fogel LJ, editors. Proceedings of the 3rd annual conference on evolutionary programming. River Edge, NJ: World Scientific; 1994. p. 131–139. Reynolds RG. An introduction to cultural algorithms. In: Sebald AV, Fogel LJ, editors. Proceedings of the 3rd annual conference on evolutionary programming. River Edge, NJ: World Scientific; 1994. p. 131–139.
31.
go back to reference Reynolds RG. Cultural algorithms: theory and applications. In: Corne D, Dorigo M, Glover F, editors. Advanced topics in computer science series: new ideas in optimization. New York: McGraw-Hill; 1999. p. 367–377. Reynolds RG. Cultural algorithms: theory and applications. In: Corne D, Dorigo M, Glover F, editors. Advanced topics in computer science series: new ideas in optimization. New York: McGraw-Hill; 1999. p. 367–377.
32.
go back to reference Smith JE. Coevolving memetic algorithms: a review and progress report. IEEE Trans Syst Man Cybern Part B. 2007;37(1):6–17.CrossRef Smith JE. Coevolving memetic algorithms: a review and progress report. IEEE Trans Syst Man Cybern Part B. 2007;37(1):6–17.CrossRef
33.
go back to reference Sotiropoulos DG, Plagianakos VP, Vrahatis MN. An evolutionary algorithm for minimizing multimodal functions. In: Proceedings of the 5th Hellenic–European conference on computer mathematics and its applications (HERCMA), Athens, Greece, September 2001, vol. 2. Athens, Greece: LEA Press; 2002. p. 496–500. Sotiropoulos DG, Plagianakos VP, Vrahatis MN. An evolutionary algorithm for minimizing multimodal functions. In: Proceedings of the 5th Hellenic–European conference on computer mathematics and its applications (HERCMA), Athens, Greece, September 2001, vol. 2. Athens, Greece: LEA Press; 2002. p. 496–500.
34.
go back to reference Solomon R. Evolutionary algorithms and gradient search: similarities and differences. IEEE Trans Evol Compu. 1998;2(2):45–55.CrossRef Solomon R. Evolutionary algorithms and gradient search: similarities and differences. IEEE Trans Evol Compu. 1998;2(2):45–55.CrossRef
35.
go back to reference Tang J, Lim M, Ong YS. Diversity-adaptive parallel memetic algorithm for solving large scale combinatorial optimization problems. Soft Comput. 2007;11(9):873–88.CrossRef Tang J, Lim M, Ong YS. Diversity-adaptive parallel memetic algorithm for solving large scale combinatorial optimization problems. Soft Comput. 2007;11(9):873–88.CrossRef
36.
go back to reference Wang H, Wang D, Yang S. A memetic algorithm with adaptive hill climbing strategy for dynamic optimization problems. Soft Comput. 2009;13:763–80.CrossRef Wang H, Wang D, Yang S. A memetic algorithm with adaptive hill climbing strategy for dynamic optimization problems. Soft Comput. 2009;13:763–80.CrossRef
37.
go back to reference Yen J, Liao JC, Lee B, Randolph D. A hybrid approach to modeling metabolic systems using a genetic algorithm and simplex method. IEEE Trans Syst Man Cybern Part B. 1998;28:173–91.CrossRef Yen J, Liao JC, Lee B, Randolph D. A hybrid approach to modeling metabolic systems using a genetic algorithm and simplex method. IEEE Trans Syst Man Cybern Part B. 1998;28:173–91.CrossRef
Metadata
Title
Memetic Algorithms
Authors
Ke-Lin Du
M. N. S. Swamy
Copyright Year
2016
DOI
https://doi.org/10.1007/978-3-319-41192-7_19

Premium Partner