Abstract
A hybrid algorithm (HA) that blends features of genetic algorithms (GA) and simulated annealing (SA) was implemented for simultaneous fits of perturbed angular correlation (PAC) spectra. The main characteristic of the HA is the incorporation of a selection criterion based on SA into the basic structure of GA. The results obtained with the HA compare favorably with fits performed with conventional methods.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Goldberg D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison Wesley, New York (1989)
Kirkpatrick, S., Gellat, C., Vecchi, M.P.: Optimization by simulated annealing. Science 220, 671–680 (1983)
Pakhira, M.K.: A hybrid genetic algorithm using probabilistic selection. J. Inst. Eng. 84, 23–30 (2003)
Lee, T.A.: Dependence of oxygen vacancy concentration in zirconia on processing parameters and reducing conditions. Dissertation, Oregon State University (2000)
Evenson, W.E., Lu, J., Winz, M.W., Gardner, J.A., Zacate, M.O., Lee, T.A., Mommer, N.: Stochastic PAC models for vacancy motions with trapping and detrapping. Hyperfine Interact. 120/121, 427–431 (1999)
Alves, M.A.: The dynamics of oxygen vacancies in zirconia: an analysis of PAC data. Dissertation, Oregon State University (2003)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Alves, M.A., Carbonari, A.W. Fitting PAC spectra with a hybrid algorithm. Hyperfine Interact 181, 127–130 (2008). https://doi.org/10.1007/s10751-008-9703-z
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10751-008-9703-z