Abstract
We present a novel Hierarchical Evolutionary Divide and Conquer method for automated, long-term planning of dietary menus. Dietary plans have to satisfy multiple numerical constraints (Reference Daily Intakes and balance on a daily and weekly basis) as well as criteria on the harmony (variety, contrast, color, appeal) of the components. Our multi-level approach solves problems via the decomposition of the search space and uses good solutions for sub-problems on higher levels of the hierarchy. Multi-Objective Genetic Algorithms are used on each level to create nutritionally adequate menus with a linear fitness combination extended with rule-based assessment. We also apply case-based initialization for starting the Genetic Algorithms from a better position of the search space. Results show that this combined strategy can cope with strict numerical constraints in a properly chosen algorithmic setup.
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© 2005 Springer-Verlag Berlin Heidelberg
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Gaál, B., Vassányi, I., Kozmann, G. (2005). An Evolutionary Divide and Conquer Method for Long-Term Dietary Menu Planning. In: Miksch, S., Hunter, J., Keravnou, E.T. (eds) Artificial Intelligence in Medicine. AIME 2005. Lecture Notes in Computer Science(), vol 3581. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527770_56
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DOI: https://doi.org/10.1007/11527770_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27831-3
Online ISBN: 978-3-540-31884-2
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