nach oben

Neural Computing and Applications

Erschienen in:

01.07.2012 | Original Article

A hybrid PBIL-based harmony search method

verfasst von: X. Z. Gao, X. Wang, T. Jokinen, S. J. Ovaska, A. Arkkio, K. Zenger

Erschienen in: Neural Computing and Applications | Ausgabe 5/2012

Einloggen

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

search-config

KI-gestützte Suche

Aus

Abstract

The harmony search (HS) method is a popular meta-heuristic optimization algorithm, which has been extensively employed to handle various engineering problems. However, it sometimes fails to offer a satisfactory convergence performance under certain circumstances. In this paper, we propose and study a hybrid HS approach, HS–PBIL, by merging the HS together with the population-based incremental learning (PBIL). Numerical simulations demonstrate that our HS–PBIL is well capable of outperforming the regular HS method in dealing with nonlinear function optimization and a practical wind generator optimization problem.

Vorheriger Artikel Targeting and synchronization at tokamak with recurrent artificial neural networks

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

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

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+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

Geem ZW, Kim JH, Loganathan GV (2001) A new heuristic optimization algorithm: harmony search. Simulation 76(2):60–68CrossRef

Lee KS, Geem ZW (2005) A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice. Comput Methods Appl Mech Eng 194(36–38):3902–3922MATHCrossRef

Kang SL, Geem ZW (2004) A new structural optimization method based on the harmony search algorithm. Comput Struct 82(9–10):781–798

Geem ZW, Kim JH, Loganathan GV (2002) Harmony search optimization: application to pipe network design. Int J Model Simul 22(2):125–133

Mahdavi M, Fesanghary M, Damangir E (2007) An improved harmony search algorithm for solving optimization problems. Appl Math Comput 188(2):1567–1579MathSciNetMATHCrossRef

Gao XZ, Wang X, Ovaska SJ (2009) Uni-modal and multi-modal optimization using modified harmony search methods. Int J Innov Comput Inf Control 5(10A):2985–2996

Gao XZ, Wang X, Ovaska SJ, Xu H (2010) A modified harmony search method in constrained optimization. Int J Innov Comput Inf Control 6(9):4235–4247

Gao XZ, Wang X, Ovaska SJ (2010) A hybrid harmony search method based on OBL. In: Proceedings of the 13th IEEE international conference on computational science and engineering, Hong Kong, China, December 2010, pp 140–145

Gao XZ, Wang X, Ovaska SJ (2010) A harmony search-based differential evolution method. In: Proceedings of the 13th IEEE international conference on computational science and engineering, Hong Kong, China, December 2010, pp 333–339

10.

Wang X, Gao XZ, Ovaska SJ (2009) Fusion of clonal selection algorithm and harmony search method in optimization of fuzzy classification systems. Int J Bioinspir Comput 1(1–2):80–88CrossRef

11.

Baluja S (1995) An empirical comparison of seven iterative and evolutionary function optimization heuristics. Technical report CMU-CS-95-193, Carnegie Mellon University

12.

Poli R, Langdon WB (2002) Foundations of genetic programming. Springer, BerlinMATH

13.

Storn R, Price K (1997) Differential evolution: a simple and efficient adaptive scheme for global optimization over continuous spaces. J Glob Optim 11:341–359MathSciNetMATHCrossRef

14.

Servet I, Travé-Massuyès L, Stern D (1997) Telephone network traffic overloading diagnosis and evolutionary computation techniques. In: Proceedings of the 3rd European conference on artificial evolution, Nimes, France, October 1997, pp 137–144

15.

Engelbrecht AP (2005) Fundamentals of computational swarm intelligence. Wiley, West Sussex

16.

Sebag M, Ducoulombier A (1988) Extending population-based incremental learning to continuous search spaces. In: Proceedings of the 5th international conference on parallel problem solving from nature, Amsterdam, The Netherlands, September 1988, pp 418–427

17.

Benchmark functions are available at http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO.htm

18.

Michalewicz Z (1996) Genetic algorithms + data structures = evolution programs, 3rd edn. Springer, BerlinMATH

19.

Ali MM, Khompatraporn C, Zabinsky ZB (2005) A numerical evaluation of several stochastic algorithms on selected continuous global optimization test problems. J Glob Optim 31(4):635–672MathSciNetMATHCrossRef

20.

Pyrhönen J, Jokinen T, Hrabovcová V (2008) Design of rotating electrical machines. Wiley, West SussexCrossRef

21.

Gao XZ, Jokinen T, Wang X, Ovaska SJ, Arkkio A (2010) A new harmony search method in optimal wind generator design. In: Proceedings of the XIX international conference on electrical machines, September 2010, Rome, Italy

22.

Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1(1):67–82CrossRef

Titel: A hybrid PBIL-based harmony search method
verfasst von: X. Z. Gao
X. Wang
T. Jokinen
S. J. Ovaska
A. Arkkio
K. Zenger
Publikationsdatum: 01.07.2012
Verlag: Springer-Verlag
Erschienen in: Neural Computing and Applications / Ausgabe 5/2012
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-011-0675-6

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

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

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Weitere Artikel der Ausgabe 5/2012

Modeling early-age hydration kinetics of Portland cement using flexible neural tree

Assessment of the quality of decisions worked out by an artificial neural network (DIAG) which diagnoses a technical object

CARTMAP: a neural network method for automated feature selection in financial time series forecasting

An FCM modeling for using a priori knowledge: application study in modeling quadruped walking

Almost periodic solution of impulsive Hopfield neural networks with finite distributed delays

Neural computing models for prediction of permeability coefficient of coarse-grained soils