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Professor John McCall


Incorporating a metropolis method in a distribution estimation using Markov random field algorithm. (2005)
Conference Proceeding
SHAKYA, S.K., MCCALL, J.A.W. and BROWN, D.F. 2005. Incorporating a metropolis method in a distribution estimation using Markov random field algorithm. In Proceedings of the 2005 IEEE congress on evolutionary computation (CEC 2005), 2-5 September 2005, Edinburgh, UK. New York: IEEE [online], volume 3, article number 1555017, pages 2576-2583. Available from: https://doi.org/10.1109/CEC.2005.1555017

Markov Random Field (MRF) modelling techniques have been recently proposed as a novel approach to probabilistic modelling for Estimation of Distribution Algorithms (EDAs)[34, 4]. An EDA using this technique, presented in [34], was called Distribution... Read More about Incorporating a metropolis method in a distribution estimation using Markov random field algorithm..

Statistical optimisation and tuning of GA factors. (2005)
Conference Proceeding
PETROVSKI, A., BROWNLEE, A. and MCCALL, J. 2005. Statistical optimisation and tuning of GA factors. In Proceedings of the 2005 IEEE congress on evolutionary computation (CEC 2005), 2-5 September 2005, Edinburgh, UK. New York: IEEE [online], volume 1, article number 1554759, pages 758-764. Available from: https://doi.org/10.1109/CEC.2005.1554759

This paper presents a practical methodology of improving the efficiency of Genetic Algorithms through tuning the factors significantly affecting GA performance. This methodology is based on the methods of statistical inference and has been successful... Read More about Statistical optimisation and tuning of GA factors..

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