Abstract
Whilst evolutionary algorithms have been well tuned for a number of different problems, finding the best combination of operational types and parameters remains an obvious challenge. In this chapter, various methodologies from the different underlying types of evolutionary algorithms are compared and contrasted in turn, particularly regarding the contribution of each option to the key processes of exploitation and exploration. The degree to which these options interact is then discussed, and an overall combination of ‘best bet’ operators is suggested. In the absence of other problem-specific information, this is recommended as a robust combination for the optimisation of future agricultural systems.
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© 2002 Springer Science+Business Media New York
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Mayer, D.G. (2002). Robust Parameters for Evolutionary Algorithms. In: Evolutionary Algorithms and Agricultural Systems. The Springer International Series in Engineering and Computer Science, vol 647. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1717-7_6
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DOI: https://doi.org/10.1007/978-1-4615-1717-7_6
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5693-6
Online ISBN: 978-1-4615-1717-7
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