An evolutionary divide and conquer method for long-term dietary menu planning

Authors:
Balázs Gaál;István Vassányi;György Kozmann
Affiliations:
Department of Information Systems, University of Veszprém, Veszprém, Hungary;Department of Information Systems, University of Veszprém, Veszprém, Hungary;Department of Information Systems, University of Veszprém, Veszprém, Hungary
Venue:
AIME'05 Proceedings of the 10th conference on Artificial Intelligence in Medicine
Year:
2005

Citing 4
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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.