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Computer vision applications - Special issue (2007)
Journal Article
Smith, L. N., Smith, M. L., Caleb-Solly, P., & Smith, J. (2007). Computer vision applications - Special issue. Image and Vision Computing, 25(7), 1035-1036. https://doi.org/10.1016/j.imavis.2007.04.001

This peer-reviewed international journal paper arose from a research collaboration which formed part of the PhD of a colleague and builds on previous conferences works [proceedings of "Adaptative Computing in Design and Manufacturing" 2002, 2005, pro... Read More about Computer vision applications - Special issue.

Parameter control in evolutionary algorithms (2007)
Journal Article
Smith, J. E., Eiben, A. E., Eiben, A., Michalewicz, Z., Schoenauer, M., & Smith, J. (2007). Parameter control in evolutionary algorithms. Studies in Computational Intelligence, 54, 19-46. https://doi.org/10.1007/978-3-540-69432-8_2

The issue of setting the values of various parameters of an evolutionary algorithm is crucial for good performance. In this paper we discuss how to do this, beginning with the issue of whether these values are best set in advance or are best changed... Read More about Parameter control in evolutionary algorithms.

On replacement strategies in steady state evolutionary algorithms (2007)
Journal Article
Smith, J. (2007). On replacement strategies in steady state evolutionary algorithms. Evolutionary Computation, 15(1), 29-59. https://doi.org/10.1162/evco.2007.15.1.29

Steady State models of Evolutionary Algorithms are widely used, yet surprisingly little attention has been paid to the effects arising from different replacement strategies. This paper explores the use of mathematical models to characterise the selec... Read More about On replacement strategies in steady state evolutionary algorithms.

Coevolving memetic algorithms: A review and progress report (2007)
Journal Article
Smith, J. E., & Smith, J. (2007). Coevolving memetic algorithms: A review and progress report. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 37(1), 6-17. https://doi.org/10.1109/TSMCB.2006.883273

Coevolving memetic algorithms are a family of metaheuristic search algorithms in which a rule-based representation of local search (LS) is coadapted alongside candidate solutions within a hybrid evolutionary system. Simple versions of these systems h... Read More about Coevolving memetic algorithms: A review and progress report.