Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Implementing Molecular Logic Gates, Circuits, and Cascades Using DNAzymes Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

20. Nature-Inspired Computation: An Unconventional Approach to Optimization

verfasst von : Xin-She Yang

Erschienen in: Advances in Unconventional Computing

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Nature-inspired computation plays an increasingly important role in many areas such as computational intelligence, optimization and data mining. From the perspective of traditional algorithms, such nature-inspired, iterative problem-solving methods are an unconventional approach to optimization. Both the number of algorithms and the popularity have increased significantly in recent years. This chapter provides a critical analysis of some nature-inspired algorithms and strives to identify the most essential characteristics among these algorithms. We also look at different algorithmic structures and ways of generating new solutions in a mathematical framework, which will provide some insight into these algorithms. We also discuss some key open problems concerning nature-inspired metaheuristics.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

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!

Jetzt informieren

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!

Jetzt informieren

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!

Jetzt informieren
Vorheriges Kapitel Memristors in Unconventional Computing: How a Biomimetic Circuit Element Can be Used to Do Bioinspired Computation
Nächstes Kapitel On Hybrid Classical and Unconventional Computing for Guiding Collective Movement
Literatur
1.
Adamatzky, A., Yang, X.S., Zhao, Y.X.: Slime mould imitates transport networks in China. Int. J. Intell. Comput. Cybern. 6(3), 232–251 (2013)MathSciNetCrossRef
2.
Adamatzky, A.: Bioevoluation of World Transport Networks. World Scientific Publishing, Singapore (2012)
3.
Ashby, W.R.: Princinples of the self-organizing sysem. In: Von Foerster, H., Zopf Jr., G.W. Pricinples of Self-Organization: Transactions of the University of Illinois Symposium. Pergamon Press, London, UK. pp. 255–278 (1962)
4.
Booker, L., Forrest, S., Mitchell, M., Riolo, R.: Perspectives on Adaptation in Natural and Artificial Systems. Oxford University Press, Oxford (2005)
5.
Blum, C., Roli, A.: Metaheuristics in combinatorial optimisation: Overview and conceptural comparision. ACM Comput. Surv. 35, 268–308 (2003)CrossRef
6.
Clerc, M., Kennedy, J.: The particle swarm – explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. Evol. Comput. 6(1), 58–73 (2002)CrossRef
7.
Dorigo, M., Di Caro, G., Gambardella, L.M.: Ant algorithms for discrite optimization. Artif. Life 5(2), 137–172 (1999)CrossRef
8.
Eiben, A.E., Smit, S.K.: Parameter tuning for configuring and analyzing evolutionary algorithms. Swarm and Evol. Comput. 1(1), 19–31 (2011)CrossRef
9.
Fister, I., Fister Jr., I., Yang, X.S., Brest, J.: A comprehensive review of firefly algorithms. Swarm and Evol. Comput. 13(1), 34–46 (2013)CrossRef
10.
Fister, I., Yang, X.-S., Brest, J., Fister Jr., I.: Modified firefly algorithm using quaternion representation. Expert Syst. Appl. 40(18), 7220–7230 (2013)CrossRef
11.
Fister, I., Yang, X.S., Fister, D., Fister Jr., I.: Firefly algorithm: A brief review of the expanding literature. Cuckoo Search and Firefly Algorithm: Theory and Applications. Studies in Computational Intelligence, pp. 347–360. Springer, Heidelberg (2014)
12.
Fister Jr., I., Yang, X.S., Fister, D., Fister, I.: Cuckoo search: a brief literature review. Cuckoo Search and Firefly Algorithm: Theory and Applications, vol. 516, pp. 49–62. Springer, Heidelber (2014)
13.
Fister Jr., I., Fister, D., Yang, X.S.: A hybrid bat algorithm. Elektrotehniski Vestnik 80(1–2), 1–7 (2013)MATH
14.
15.
16.
Geem, Z.W., Kim, J.H., Loganathan, G.V.: A new heuristic optimization: harmony search. Simulation 76(2), 60–68 (2001)CrossRef
17.
Holland, J.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Anbor (1975)
18.
Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ, pp. 1942–1948 (1995)
19.
Passino, K.M.: Bactorial foraging optimization. Int. J. Swarm Intell. Res. 1(1), 1–16 (2010)CrossRef
20.
21.
Price, K., Storn, R., Lampinen, J.: Differential Evolution: A Practical Approach to Global Optimization. Springer, Berlin (2005)MATH
22.
Senthilnath, J., Omkar, S.N., Mani, V.: Clustering using firely algorithm: performance study. Swarm Evol. Comput. 1(3), 164–171 (2011)CrossRef
23.
Shi, Y.H., Eberhart, R.: A modified particle swarm optimizer. In: Proceedings of the 1998 IEEE World Congress on Computational Intelligence, 4–9 May 1998, Anchorage, AK, IEEE Press, USA, pp. 69-73 (1998)
24.
Storn, R.: On the usage of differential evolution for function optimization. In: Proceedings of the Biennial Conference of the North American Fuzzy Information Processing Society (NAFIPS). Berkeley, CA 1996, pp. 519–523 (1996)
25.
Storn, R., Price, K.: Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces. J. Glob. Optim. 11(4), 341–359 (1997)MathSciNetCrossRefMATH
26.
Wang, F., He, X.S., Wang, Y., Yang, S.M.: Markov model and convergence analysis based on cuckoo search algorithm. Comput. Eng. 38(11), 180–185 (2012). (in Chinese)
27.
Wolpert, D.H., Macready, W.G.: No free lunch theorems for optimization. IEEE Trans. Evol. Comput. 1(1), 67–82 (1997)CrossRef
28.
Yang, X.S.: Nature-Inspired Metaheuristic Algorithms. Luniver Press, Bristol (2008)
29.
Yang, X.S.: A new metaheuristic bat-inspired algorithm. In: Nature Inspired Cooperative Strategies for Optimisation (NICSO 2010). Studies in Computational Intelligence, vol. 284, pp. 65-74. Springer, Heidelberg (2010)
30.
Yang, X.S.: Bat algorithm for multi-objective optimisation. Int. J. Bio-Inspired Comput. 3(5), 267–274 (2011)CrossRef
31.
Yang, X.S., Deb, S., Fong, S.: Accelerated particle swarm optimization and support vector machine for business optimization and applications. In: Networked Digital Technologies 2011, Communications in Computer and Information Science, vol. 136, pp. 53–66. Springer, Heidelberg (2011)
32.
Yang, X.S., Gandomi, A.H.: Bat algorithm: a novel approach for global engineering optimization. Eng. Comput. 29(5), 1–18 (2012)CrossRef
33.
Yang, X.S.: Flower pollination algorithm for global optimization. In: Unconventional Computation and Natural Computation, pp. 240–249. Springer, Heidelberg (2012)
34.
Yang, X.S., Deb, S.: Cuckoo search via Lévy flights. In: Proceeings of World Congress on Nature & Biologically Inspired Computing (NaBIC 2009), pp. 210–214. IEEE Publications, USA (2009)
35.
Yang, X.S., Deb, S.: Engineering optimization by cuckoo search. Int. J. Math. Modelling Numer. Optim. 1(4), 330–343 (2010)CrossRefMATH
36.
Yang, X.S., Deb, S.: Multiobjective cuckoo search for design optimization. In: Computers and Operations Research, 40(6), pp. 1616-1624 (2013)
37.
Yang, X.S., Deb, S.: Cuckoo search: recent advances and applications. Neural Comput. Appl. 24(1), 169–174 (2014)CrossRef
38.
Yang, X.S., Deb, S., Loomes, M., Karamanoglu, M.: A framework for self-tuning optimization algorithm. Neural Comput. Appl. 23(7–8), 2051–2057 (2013)CrossRef
39.
Yang, X.S., Karamanoglu, M., He, X.S.: Flower pollination algorithm: a novel approach for multiobjective optimization. Eng. Optim. 46(9), 1222–1237 (2014)MathSciNetCrossRef
40.
Yang, X.S.: Nature-Inspired Optimization Algorithms. Elsevier, London (2014)MATH
41.
Yousif, A., Abdullah, A.H., Nor, S.M., Abdelaziz, A.A.: Scheduling jobs on grid computing using firefly algorithm. J. Theoret. Appl. Inf. Technol. 33(2), 155–164 (2011)
42.
Metadaten
Titel
Nature-Inspired Computation: An Unconventional Approach to Optimization
verfasst von
Xin-She Yang
Copyright-Jahr
2017
Buch
Advances in Unconventional Computing

Print ISBN: 978-3-319-33920-7

Electronic ISBN: 978-3-319-33921-4

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-33921-4_20

Premium Partner

    Bildnachweise